docs(perception): record M4.8R2 occupancy gate

apps/control-station/src/core/laboratory/advancedIndex.ts

@@ -42,12 +42,14 @@ import {
   fetchM48LifecycleResult,
 } from "./m48ObjectCentricQuality";
 import { fetchM48SmallStaticRegression } from "./m48SmallStaticRegression";
+import { fetchM48StaticOccupancyQualification } from "./m48StaticOccupancyQualification";
 import { fetchM48SFixedClassDetectorResult } from "./m48sFixedClassDetector";
 import { fetchM48TRiskQualityResult } from "./m48tRiskQuality";
 
 export type AdvancedLaboratoryWorkId =
   | "m48-object-centric-quality"
   | "m48-small-static-passage-regression"
+  | "m48-static-occupancy-qualification"
   | "m48s-fixed-class-detector"
   | "m48t-risk-quality-temporal"
   | "m47-reference-graph-shadow"
@@ -94,6 +96,7 @@ export interface AdvancedLaboratoryIndexItem {
 const WORK_IDS: readonly AdvancedLaboratoryWorkId[] = [
   "m48-object-centric-quality",
   "m48-small-static-passage-regression",
+  "m48-static-occupancy-qualification",
   "m48s-fixed-class-detector",
   "m48t-risk-quality-temporal",
   "m47-reference-graph-shadow",
@@ -135,8 +138,9 @@ const WORK_IDS: readonly AdvancedLaboratoryWorkId[] = [
 const RESULT_PREFIX: Readonly<Record<AdvancedLaboratoryWorkId, string>> = {
   "m48-object-centric-quality": "m48-object-quality-(?:pack|result)",
   "m48-small-static-passage-regression": "m48-small-static-passage-regression",
+  "m48-static-occupancy-qualification": "m48-static-occupancy-qualification",
   "m48s-fixed-class-detector": "m48s-fixed-class-detector-lab",
-  "m48t-risk-quality-temporal": "m48t-risk-quality-temporal-lab",
+  "m48t-risk-quality-temporal": "(?:m48t-risk-quality-temporal-lab|m48q-native-risk-quality-lab)",
   "m47-reference-graph-shadow": "m47-reference-graph-lab",
   "m4-replay-threat": "m4-threat-replay",
   "l3-pointpillars-visual-audit": "l3-pointpillars-visual-audit",
@@ -184,6 +188,7 @@ export function emptyAdvancedLaboratoryResults(): AdvancedLaboratoryResults {
     m47Graph: null,
     m48: null,
     m48SmallStatic: null,
+    m48StaticOccupancy: null,
     m48s: null,
     m48t: null,
     m4Threat: null,
@@ -312,6 +317,7 @@ export function advancedLaboratoryResultAvailable(
 ): boolean {
   return workId === "m48-object-centric-quality" ? results.m48 !== null
     : workId === "m48-small-static-passage-regression" ? results.m48SmallStatic !== null
+    : workId === "m48-static-occupancy-qualification" ? results.m48StaticOccupancy !== null
     : workId === "m48s-fixed-class-detector" ? results.m48s !== null
     : workId === "m48t-risk-quality-temporal" ? results.m48t !== null
     : workId === "m47-reference-graph-shadow" ? results.m47Graph !== null
@@ -369,6 +375,9 @@ export async function fetchAdvancedLaboratoryResult(
   } else if (workId === "m48-small-static-passage-regression") {
     if (!resultId) throw new AdvancedLaboratoryContractError("M4.8R1 regression identity не выбрана.");
     results.m48SmallStatic = await fetchM48SmallStaticRegression(resultId, { fetcher, signal });
+  } else if (workId === "m48-static-occupancy-qualification") {
+    if (!resultId) throw new AdvancedLaboratoryContractError("M4.8R2 qualification identity не выбрана.");
+    results.m48StaticOccupancy = await fetchM48StaticOccupancyQualification(resultId, { fetcher, signal });
   } else if (workId === "m48s-fixed-class-detector") {
     if (!resultId) throw new AdvancedLaboratoryContractError("M4.8S LAB identity не выбрана.");
     results.m48s = await fetchM48SFixedClassDetectorResult(resultId, { fetcher, signal });

apps/control-station/src/core/laboratory/advancedLaboratoryResults.ts

@@ -36,6 +36,7 @@ import type { M4ThreatReplayResult } from "./m4ReplayThreat";
 import type { M47ReferenceGraphLabResult } from "./m47ReferenceGraph";
 import type { M48AdvancedResult } from "./m48ObjectCentricQuality";
 import type { M48SmallStaticRegressionResult } from "./m48SmallStaticRegression";
+import type { M48StaticOccupancyQualificationResult } from "./m48StaticOccupancyQualification";
 import type { M48SFixedClassDetectorResult } from "./m48sFixedClassDetector";
 import type { M48TRiskQualityResult } from "./m48tRiskQuality";
 
@@ -43,6 +44,7 @@ export interface AdvancedLaboratoryResults {
   m47Graph: M47ReferenceGraphLabResult | null;
   m48: M48AdvancedResult | null;
   m48SmallStatic: M48SmallStaticRegressionResult | null;
+  m48StaticOccupancy: M48StaticOccupancyQualificationResult | null;
   m48s: M48SFixedClassDetectorResult | null;
   m48t: M48TRiskQualityResult | null;
   m4Threat: M4ThreatReplayResult | null;

apps/control-station/src/core/laboratory/advancedResults.ts

@@ -967,10 +967,9 @@ export async function fetchAdvancedLaboratoryResults({
   const e39 = settledCatalogValue(settled[7]);
   const e40 = settledCatalogValue(settled[8]);
   return {
-    m47Graph: null, m48: null, m48SmallStatic: null, m48s: null, m48t: null, m4Threat: null,
-    l3: null, l31: null,
-    l32: null,
-    l33: null,
+    m47Graph: null, m48: null, m48SmallStatic: null, m48StaticOccupancy: null,
+    m48s: null, m48t: null, m4Threat: null,
+    l3: null, l31: null, l32: null, l33: null,
     e31,
     e32,
     e33,

apps/control-station/src/core/laboratory/m48StaticOccupancyQualification.ts

@@ -0,0 +1,248 @@
+import type { LaboratoryFetch } from "./advancedResults";
+import type { M48Authority } from "./m48ObjectCentricQuality";
+
+const RESULT_ID = /^m48-static-occupancy-qualification-[a-f0-9]{64}$/;
+const M47_RESULT_ID = /^m47-reference-graph-lab-[a-f0-9]{64}$/;
+const M48R1_RESULT_ID = /^m48-small-static-passage-regression-[a-f0-9]{64}$/;
+const ANCHOR_ID = /^anchor-[a-f0-9]{24}$/;
+
+export interface M48StaticOccupancyMetrics {
+  operatorStaticAnchorCount: number;
+  baselineQualifiedCount: number;
+  candidateQualifiedCount: number;
+  unresolvedUnknownCount: number;
+  criticalNearAnchorCount: number;
+  criticalNearBaselineRecall: number;
+  criticalNearCandidateRecall: number;
+  approachAnchorCount: number;
+  approachBaselineRecall: number;
+  approachCandidateRecall: number;
+  canonicalEngineeringAnchorCount: number;
+  canonicalEngineeringRecall: number;
+  falseFreeCount: number;
+}
+
+export interface M48StaticOccupancyQualificationResult {
+  resultId: string;
+  referenceGraphLabResultId: string;
+  smallStaticResultId: string;
+  createdAtUtc: string;
+  runLabel: "M4.8R2";
+  pipelineId: "m4-current-rolling-plus-step-static-occupancy/v1";
+  experimentId: "m48-static-occupancy-qualification/v1";
+  accepted: boolean;
+  metrics: M48StaticOccupancyMetrics;
+  gates: {
+    criticalNearCandidateRecall: boolean;
+    approachCandidateRecall: boolean;
+    canonicalEngineeringRecall: boolean;
+    zeroFalseFree: boolean;
+    independentTruthAvailable: false;
+  };
+  decision: {
+    state: "accepted-bounded-static-occupancy-qualification" | "partial-static-occupancy-qualification";
+    criticalNearCandidateReadyForShadow: boolean;
+    productionAccepted: false;
+    summary: string;
+    nextAction: string;
+  };
+  authority: M48Authority;
+}
+
+export interface M48StaticOccupancyCase {
+  anchorId: string;
+  clipId: string;
+  sequence: number;
+  extentXyxy: readonly [number, number, number, number];
+  distanceM: number;
+  distanceBand: "critical-near" | "approach" | "outside-qualified-bands";
+  baselineQualified: boolean;
+  candidateQualified: boolean;
+  outcome: "candidate-qualified" | "unresolved-unknown-never-free";
+  graphMatched: boolean;
+}
+
+export class M48StaticOccupancyContractError extends Error {}
+
+function objectValue(value: unknown, label: string): Record<string, unknown> {
+  if (!value || typeof value !== "object" || Array.isArray(value)) {
+    throw new M48StaticOccupancyContractError(`${label}: ожидался объект.`);
+  }
+  return value as Record<string, unknown>;
+}
+
+function text(value: unknown, label: string): string {
+  if (typeof value !== "string" || !value.trim()) {
+    throw new M48StaticOccupancyContractError(`${label}: ожидалась строка.`);
+  }
+  return value;
+}
+
+function numberValue(value: unknown, label: string): number {
+  if (typeof value !== "number" || !Number.isFinite(value)) {
+    throw new M48StaticOccupancyContractError(`${label}: ожидалось число.`);
+  }
+  return value;
+}
+
+function integer(value: unknown, label: string): number {
+  const parsed = numberValue(value, label);
+  if (!Number.isInteger(parsed) || parsed < 0) {
+    throw new M48StaticOccupancyContractError(`${label}: ожидалось целое число.`);
+  }
+  return parsed;
+}
+
+function bool(value: unknown, label: string): boolean {
+  if (typeof value !== "boolean") {
+    throw new M48StaticOccupancyContractError(`${label}: ожидался флаг.`);
+  }
+  return value;
+}
+
+function exact(value: unknown, expected: string | boolean, label: string): void {
+  if (value !== expected) throw new M48StaticOccupancyContractError(`${label}: нарушен контракт.`);
+}
+
+function member<T extends string>(value: unknown, allowed: readonly T[], label: string): T {
+  const parsed = text(value, label);
+  if (!allowed.includes(parsed as T)) {
+    throw new M48StaticOccupancyContractError(`${label}: недопустимое значение.`);
+  }
+  return parsed as T;
+}
+
+function extent(value: unknown): readonly [number, number, number, number] {
+  if (!Array.isArray(value) || value.length !== 4 || value.some((item) => typeof item !== "number" || !Number.isFinite(item))) {
+    throw new M48StaticOccupancyContractError("M4.8R2.case.extent: нарушен контракт.");
+  }
+  const result = value as number[];
+  if (result.some((item) => item < 0 || item > 1) || result[0]! >= result[2]! || result[1]! >= result[3]!) {
+    throw new M48StaticOccupancyContractError("M4.8R2.case.extent: нарушена геометрия.");
+  }
+  return result as unknown as readonly [number, number, number, number];
+}
+
+function authority(value: unknown): M48Authority {
+  const row = objectValue(value, "M4.8R2.authority");
+  exact(row.mode, "replay-simulated", "M4.8R2.authority.mode");
+  exact(row.physical_live, false, "M4.8R2.authority.physical_live");
+  exact(row.commands_enabled, false, "M4.8R2.authority.commands_enabled");
+  exact(row.actuation_allowed, false, "M4.8R2.authority.actuation_allowed");
+  exact(row.navigation_or_safety_accepted, false, "M4.8R2.authority.navigation_or_safety_accepted");
+  return { mode: "replay-simulated", physicalLive: false, commandsEnabled: false, actuationAllowed: false, navigationOrSafetyAccepted: false };
+}
+
+function metrics(value: unknown): M48StaticOccupancyMetrics {
+  const row = objectValue(value, "M4.8R2.metrics");
+  return {
+    operatorStaticAnchorCount: integer(row.operator_static_anchor_count, "operator_static_anchor_count"),
+    baselineQualifiedCount: integer(row.baseline_qualified_count, "baseline_qualified_count"),
+    candidateQualifiedCount: integer(row.candidate_qualified_count, "candidate_qualified_count"),
+    unresolvedUnknownCount: integer(row.unresolved_unknown_count, "unresolved_unknown_count"),
+    criticalNearAnchorCount: integer(row.critical_near_anchor_count, "critical_near_anchor_count"),
+    criticalNearBaselineRecall: numberValue(row.critical_near_baseline_recall, "critical_near_baseline_recall"),
+    criticalNearCandidateRecall: numberValue(row.critical_near_candidate_recall, "critical_near_candidate_recall"),
+    approachAnchorCount: integer(row.approach_anchor_count, "approach_anchor_count"),
+    approachBaselineRecall: numberValue(row.approach_baseline_recall, "approach_baseline_recall"),
+    approachCandidateRecall: numberValue(row.approach_candidate_recall, "approach_candidate_recall"),
+    canonicalEngineeringAnchorCount: integer(row.canonical_engineering_anchor_count, "canonical_engineering_anchor_count"),
+    canonicalEngineeringRecall: numberValue(row.canonical_engineering_recall, "canonical_engineering_recall"),
+    falseFreeCount: integer(row.false_free_count, "false_free_count"),
+  };
+}
+
+export async function fetchM48StaticOccupancyQualification(
+  resultId: string,
+  { fetcher = fetch, signal }: { fetcher?: LaboratoryFetch; signal?: AbortSignal } = {},
+): Promise<M48StaticOccupancyQualificationResult> {
+  if (!RESULT_ID.test(resultId)) throw new M48StaticOccupancyContractError("M4.8R2 identity недопустима.");
+  const response = await fetcher(`/api/v1/laboratory/m48/regressions/static-occupancy/${encodeURIComponent(resultId)}`, { method: "GET", headers: { Accept: "application/json" }, signal });
+  if (!response.ok) throw new M48StaticOccupancyContractError(`M4.8R2 недоступен: HTTP ${response.status}.`);
+  const payload = objectValue(await response.json(), "M4.8R2");
+  exact(payload.schema_version, "missioncore.m48-static-occupancy-qualification-result-view/v1", "M4.8R2.schema_version");
+  const m47 = text(payload.reference_graph_lab_result_id, "M4.8R2.reference_graph_lab_result_id");
+  const m48r1 = text(payload.small_static_result_id, "M4.8R2.small_static_result_id");
+  if (!M47_RESULT_ID.test(m47) || !M48R1_RESULT_ID.test(m48r1)) throw new M48StaticOccupancyContractError("M4.8R2 source identity нарушена.");
+  exact(payload.run_label, "M4.8R2", "M4.8R2.run_label");
+  exact(payload.pipeline_id, "m4-current-rolling-plus-step-static-occupancy/v1", "M4.8R2.pipeline_id");
+  exact(payload.experiment_id, "m48-static-occupancy-qualification/v1", "M4.8R2.experiment_id");
+  exact(payload.ground_truth, false, "M4.8R2.ground_truth");
+  exact(payload.independent_truth, false, "M4.8R2.independent_truth");
+  const gates = objectValue(payload.gates, "M4.8R2.gates");
+  const decision = objectValue(payload.decision, "M4.8R2.decision");
+  exact(decision.production_accepted, false, "M4.8R2.decision.production_accepted");
+  return {
+    resultId,
+    referenceGraphLabResultId: m47,
+    smallStaticResultId: m48r1,
+    createdAtUtc: text(payload.created_at_utc, "M4.8R2.created_at_utc"),
+    runLabel: "M4.8R2",
+    pipelineId: "m4-current-rolling-plus-step-static-occupancy/v1",
+    experimentId: "m48-static-occupancy-qualification/v1",
+    accepted: bool(payload.accepted, "M4.8R2.accepted"),
+    metrics: metrics(payload.metrics),
+    gates: {
+      criticalNearCandidateRecall: bool(gates.critical_near_candidate_recall, "critical_near_candidate_recall"),
+      approachCandidateRecall: bool(gates.approach_candidate_recall, "approach_candidate_recall"),
+      canonicalEngineeringRecall: bool(gates.canonical_engineering_recall, "canonical_engineering_recall"),
+      zeroFalseFree: bool(gates.zero_false_free, "zero_false_free"),
+      independentTruthAvailable: false,
+    },
+    decision: {
+      state: member(
+        decision.state,
+        [
+          "accepted-bounded-static-occupancy-qualification",
+          "partial-static-occupancy-qualification",
+        ] as const,
+        "M4.8R2.decision.state",
+      ),
+      criticalNearCandidateReadyForShadow: bool(decision.critical_near_candidate_ready_for_shadow, "critical_near_candidate_ready_for_shadow"),
+      productionAccepted: false,
+      summary: text(decision.summary, "M4.8R2.decision.summary"),
+      nextAction: text(decision.next_action, "M4.8R2.decision.next_action"),
+    },
+    authority: authority(payload.authority),
+  };
+}
+
+export async function fetchM48StaticOccupancyCases(
+  resultId: string,
+  { fetcher = fetch, signal }: { fetcher?: LaboratoryFetch; signal?: AbortSignal } = {},
+): Promise<readonly M48StaticOccupancyCase[]> {
+  if (!RESULT_ID.test(resultId)) throw new M48StaticOccupancyContractError("M4.8R2 identity недопустима.");
+  const response = await fetcher(`/api/v1/laboratory/m48/regressions/static-occupancy/${encodeURIComponent(resultId)}/cases`, { method: "GET", headers: { Accept: "application/json" }, signal });
+  if (!response.ok) throw new M48StaticOccupancyContractError(`M4.8R2 cases недоступны: HTTP ${response.status}.`);
+  const payload = objectValue(await response.json(), "M4.8R2 cases");
+  exact(payload.schema_version, "missioncore.m48-static-occupancy-case-catalog/v1", "M4.8R2 cases.schema_version");
+  if (!Array.isArray(payload.cases) || payload.cases.length !== integer(payload.case_count, "M4.8R2.case_count")) throw new M48StaticOccupancyContractError("M4.8R2 cases: размер изменился.");
+  return payload.cases.map((value, index) => {
+    const row = objectValue(value, `M4.8R2.case[${index}]`);
+    const anchorId = text(row.anchor_id, "anchor_id");
+    if (!ANCHOR_ID.test(anchorId)) throw new M48StaticOccupancyContractError("M4.8R2 anchor identity нарушена.");
+    const graph = objectValue(row.accepted_graph, "accepted_graph");
+    const band = member(
+      row.distance_band,
+      ["critical-near", "approach", "outside-qualified-bands"] as const,
+      "distance_band",
+    );
+    const outcome = member(
+      row.outcome,
+      ["candidate-qualified", "unresolved-unknown-never-free"] as const,
+      "outcome",
+    );
+    return {
+      anchorId,
+      clipId: text(row.clip_id, "clip_id"),
+      sequence: integer(row.sequence, "sequence"),
+      extentXyxy: extent(row.extent_xyxy),
+      distanceM: numberValue(row.distance_m, "distance_m"),
+      distanceBand: band,
+      baselineQualified: bool(row.baseline_qualified, "baseline_qualified"),
+      candidateQualified: bool(row.candidate_qualified, "candidate_qualified"),
+      outcome,
+      graphMatched: bool(graph.matched, "accepted_graph.matched"),
+    };
+  });
+}

apps/control-station/src/core/laboratory/m48tRiskQuality.ts

@@ -19,7 +19,8 @@ export interface M48TReviewCase {
   sha256: string;
 }
 
-export interface M48TRiskQualityResult {
+export interface M48TLegacyRiskQualityResult {
+  variant: "legacy-coco-quality";
   resultId: string;
   createdAtUtc: string;
   source: {
@@ -93,6 +94,90 @@ export interface M48TRiskQualityResult {
   limitations: readonly string[];
 }
 
+export type M48QRiskFamily = "person" | "animal" | "light-road-user" | "vehicle";
+
+export interface M48QNativeProposal {
+  proposalId: string;
+  className: string;
+  riskFamily: M48QRiskFamily;
+  score: number;
+  boxXyxy: readonly [number, number, number, number];
+}
+
+export interface M48QNativeReviewCase {
+  caseId: string;
+  sequence: number;
+  frameId: string;
+  evidenceTimeNs: number;
+  imageUrl: string;
+  width: 800;
+  height: 600;
+  byteLength: number;
+  sha256: string;
+  selectionBuckets: readonly string[];
+  nativeDetectionCount: number;
+  legacyDetectionCount: number;
+  matchedDetectionCount: number;
+  proposals: readonly M48QNativeProposal[];
+}
+
+export interface M48QNativeRiskQualityResult {
+  variant: "native-risk-review";
+  resultId: string;
+  createdAtUtc: string;
+  source: {
+    sourceId: "RAVNOVES00";
+    frameCount: 4489;
+    width: 800;
+    height: 600;
+    geometricResampling: false;
+  };
+  candidate: {
+    providerId: string;
+    modelId: "rf_detr_large_native_kb4:1";
+    preprocessId: "raw-kb4-uint8-fused-mask-rgb-pad8-imagenet-trt/v0";
+    minimumScore: 0.25;
+  };
+  execution: {
+    effectiveWorldStateFps: number;
+    worldStateCompletionP95Ms: number;
+    detectorTotalP95Ms: number;
+    gpuUtilizationP95Percent: number;
+    gpuMemoryMaximumMib: number;
+    additionalInferencePasses: 0;
+  };
+  selection: {
+    caseCount: 24;
+    minimumSequenceSeparation: number;
+    bucketCoverage: Readonly<Record<string, number>>;
+    classCounts: Readonly<Record<string, number>>;
+  };
+  runtime: {
+    deliveryRatio: number;
+    integratedGatePassed: true;
+    operatingTargetGatePassed: true;
+  };
+  parity: {
+    precision: number;
+    recall: number;
+    meanIou: number;
+  };
+  acceptance: {
+    reviewReady: true;
+    independentQualityEvaluated: false;
+    semanticCandidateAccepted: false;
+  };
+  review: {
+    cases: readonly M48QNativeReviewCase[];
+  };
+  method: M48TLaboratoryMethod;
+  limitations: readonly string[];
+}
+
+export type M48TRiskQualityResult =
+  | M48TLegacyRiskQualityResult
+  | M48QNativeRiskQualityResult;
+
 type LaboratoryFetch = (input: RequestInfo | URL, init?: RequestInit) => Promise<Response>;
 
 export class M48TContractError extends Error {}
@@ -173,9 +258,10 @@ function method(value: unknown): M48TLaboratoryMethod {
   };
 }
 
-function parseResult(value: unknown, expectedResultId: string): M48TRiskQualityResult {
+function parseLegacyResult(value: unknown, expectedResultId: string): M48TLegacyRiskQualityResult {
   const raw = object(value, "M4.8T result");
   exact(raw.schema_version, "missioncore.m48t-risk-quality-temporal-view/v1", "M4.8T schema");
+  exact(raw.variant, "legacy-coco-quality", "M4.8T variant");
   exact(raw.result_id, expectedResultId, "M4.8T identity");
   exact(raw.status, "complete-quality-gate-failed-temporal-invariant-passed", "M4.8T status");
   exact(raw.access, "read-only", "M4.8T access");
@@ -234,6 +320,7 @@ function parseResult(value: unknown, expectedResultId: string): M48TRiskQualityR
   for (const [key, count] of Object.entries(failures)) parsedFailures[key] = integer(count, `M4.8T failure ${key}`);
   const temporalConfiguration = object(configuration.temporal, "M4.8T temporal configuration");
   return {
+    variant: "legacy-coco-quality",
     resultId: expectedResultId,
     createdAtUtc: text(raw.created_at_utc, "M4.8T created at"),
     source: {
@@ -306,6 +393,207 @@ function parseResult(value: unknown, expectedResultId: string): M48TRiskQualityR
   };
 }
 
+function numberRecord(value: unknown, label: string): Readonly<Record<string, number>> {
+  const raw = object(value, label);
+  const parsed: Record<string, number> = {};
+  for (const [key, item] of Object.entries(raw)) parsed[key] = integer(item, `${label}.${key}`);
+  return parsed;
+}
+
+function nativeRiskFamily(value: unknown): M48QRiskFamily {
+  const parsed = text(value, "M4.8Q risk family");
+  if (!["person", "animal", "light-road-user", "vehicle"].includes(parsed)) {
+    throw new M48TContractError("M4.8Q risk family: неизвестное значение.");
+  }
+  return parsed as M48QRiskFamily;
+}
+
+function nativeProposal(value: unknown): M48QNativeProposal {
+  const raw = object(value, "M4.8Q proposal");
+  const coordinates = array(raw.box_xyxy, "M4.8Q proposal box").map((item) =>
+    number(item, "M4.8Q proposal coordinate")
+  );
+  if (
+    coordinates.length !== 4
+    || coordinates[0] >= coordinates[2]
+    || coordinates[1] >= coordinates[3]
+    || coordinates[2] > 800
+    || coordinates[3] > 600
+  ) {
+    throw new M48TContractError("M4.8Q proposal box: нарушена raw-raster геометрия.");
+  }
+  const score = number(raw.score, "M4.8Q proposal score");
+  if (score < 0.25 || score > 1) throw new M48TContractError("M4.8Q proposal score: нарушен threshold.");
+  return {
+    proposalId: text(raw.proposal_id, "M4.8Q proposal id"),
+    className: text(raw.class_name, "M4.8Q proposal class"),
+    riskFamily: nativeRiskFamily(raw.risk_family),
+    score,
+    boxXyxy: coordinates as [number, number, number, number],
+  };
+}
+
+function parseNativeResult(value: unknown, expectedResultId: string): M48QNativeRiskQualityResult {
+  const raw = object(value, "M4.8Q result");
+  exact(raw.schema_version, "missioncore.m48q-native-risk-quality-view/v1", "M4.8Q schema");
+  exact(raw.variant, "native-risk-review", "M4.8Q variant");
+  exact(raw.result_id, expectedResultId, "M4.8Q identity");
+  exact(raw.status, "complete-review-ready-quality-not-adjudicated", "M4.8Q status");
+  exact(raw.access, "read-only", "M4.8Q access");
+  exact(raw.ground_truth, false, "M4.8Q ground truth");
+
+  const source = object(raw.source, "M4.8Q source");
+  exact(source.source_id, "RAVNOVES00", "M4.8Q source id");
+  exact(source.frame_count, 4489, "M4.8Q source frames");
+  exact(source.raster_width, 800, "M4.8Q source width");
+  exact(source.raster_height, 600, "M4.8Q source height");
+  exact(source.geometric_resampling, false, "M4.8Q source resampling");
+  exact(source.rectification, false, "M4.8Q source rectification");
+  exact(source.warp, false, "M4.8Q source warp");
+
+  const configuration = object(raw.configuration, "M4.8Q configuration");
+  const candidate = object(configuration.candidate, "M4.8Q candidate");
+  const execution = object(raw.execution, "M4.8Q execution");
+  const metrics = object(raw.metrics, "M4.8Q metrics");
+  const selection = object(metrics.selection, "M4.8Q selection");
+  const runtime = object(metrics.runtime, "M4.8Q runtime");
+  const parity = object(metrics.native_tensor_parity, "M4.8Q parity");
+  const acceptance = object(raw.acceptance, "M4.8Q acceptance");
+  exact(acceptance.review_ready, true, "M4.8Q review readiness");
+  exact(acceptance.integrated_runtime_gate_passed, true, "M4.8Q runtime gate");
+  exact(acceptance.independent_quality_evaluated, false, "M4.8Q quality state");
+  exact(acceptance.semantic_candidate_accepted, false, "M4.8Q candidate state");
+  exact(selection.case_count, 24, "M4.8Q selected cases");
+
+  const review = object(raw.review, "M4.8Q review");
+  const raster = object(review.source_raster, "M4.8Q review raster");
+  exact(raster.width, 800, "M4.8Q review width");
+  exact(raster.height, 600, "M4.8Q review height");
+  const overlay = object(review.overlay, "M4.8Q overlay");
+  exact(overlay.client_rendered, true, "M4.8Q client overlay");
+  exact(overlay.toggleable, true, "M4.8Q overlay toggle");
+  const cases = array(review.cases, "M4.8Q review cases").map((value) => {
+    const item = object(value, "M4.8Q review case");
+    const caseId = text(item.case_id, "M4.8Q case id");
+    if (!/^[0-9]{6}$/.test(caseId)) throw new M48TContractError("M4.8Q case identity нарушена.");
+    const sequence = integer(item.sequence, "M4.8Q case sequence");
+    exact(caseId, sequence.toString().padStart(6, "0"), "M4.8Q case/sequence identity");
+    exact(item.frame_id, `frame-${caseId}`, "M4.8Q frame identity");
+    exact(item.media_type, "image/jpeg", "M4.8Q case media");
+    exact(item.width, 800, "M4.8Q case width");
+    exact(item.height, 600, "M4.8Q case height");
+    exact(item.geometric_resampling, false, "M4.8Q case resampling");
+    const comparison = object(item.comparison, "M4.8Q comparison");
+    const proposals = array(item.proposals, "M4.8Q proposals").map(nativeProposal);
+    if (!proposals.length) throw new M48TContractError("M4.8Q proposals: пустой review case.");
+    return {
+      caseId,
+      sequence,
+      frameId: `frame-${caseId}`,
+      evidenceTimeNs: integer(item.evidence_time_ns, "M4.8Q evidence time"),
+      imageUrl: text(item.image_url, "M4.8Q image URL"),
+      width: 800 as const,
+      height: 600 as const,
+      byteLength: integer(item.byte_length, "M4.8Q image bytes"),
+      sha256: sha(item.sha256, "M4.8Q image SHA"),
+      selectionBuckets: array(item.selection_buckets, "M4.8Q selection buckets").map((bucket) =>
+        text(bucket, "M4.8Q selection bucket")
+      ),
+      nativeDetectionCount: integer(comparison.native_detection_count, "M4.8Q native count"),
+      legacyDetectionCount: integer(comparison.legacy_704_detection_count, "M4.8Q legacy count"),
+      matchedDetectionCount: integer(
+        comparison.matched_detection_count_iou_at_least_0_5,
+        "M4.8Q matched count",
+      ),
+      proposals,
+    };
+  });
+  if (cases.length !== 24 || new Set(cases.map(({ caseId }) => caseId)).size !== 24) {
+    throw new M48TContractError("M4.8Q review catalog: нарушен размер.");
+  }
+
+  return {
+    variant: "native-risk-review",
+    resultId: expectedResultId,
+    createdAtUtc: text(raw.created_at_utc, "M4.8Q created at"),
+    source: {
+      sourceId: "RAVNOVES00",
+      frameCount: 4489,
+      width: 800,
+      height: 600,
+      geometricResampling: false,
+    },
+    candidate: {
+      providerId: text(candidate.provider_id, "M4.8Q provider"),
+      modelId: exact(candidate.model_id, "rf_detr_large_native_kb4:1", "M4.8Q model"),
+      preprocessId: exact(
+        candidate.preprocess_id,
+        "raw-kb4-uint8-fused-mask-rgb-pad8-imagenet-trt/v0",
+        "M4.8Q preprocess",
+      ),
+      minimumScore: exact(candidate.minimum_score, 0.25, "M4.8Q threshold"),
+    },
+    execution: {
+      effectiveWorldStateFps: number(execution.effective_world_state_fps, "M4.8Q FPS"),
+      worldStateCompletionP95Ms: number(
+        execution.world_state_completion_p95_ms,
+        "M4.8Q world-state p95",
+      ),
+      detectorTotalP95Ms: number(execution.detector_total_p95_ms, "M4.8Q detector p95"),
+      gpuUtilizationP95Percent: number(
+        execution.gpu_utilization_p95_percent,
+        "M4.8Q GPU p95",
+      ),
+      gpuMemoryMaximumMib: number(
+        execution.gpu_memory_used_maximum_mib,
+        "M4.8Q VRAM maximum",
+      ),
+      additionalInferencePasses: exact(
+        execution.additional_inference_passes,
+        0,
+        "M4.8Q inference passes",
+      ),
+    },
+    selection: {
+      caseCount: 24,
+      minimumSequenceSeparation: integer(
+        selection.minimum_sequence_separation,
+        "M4.8Q case separation",
+      ),
+      bucketCoverage: numberRecord(selection.selected_bucket_coverage, "M4.8Q bucket coverage"),
+      classCounts: numberRecord(selection.selected_class_counts, "M4.8Q class counts"),
+    },
+    runtime: {
+      deliveryRatio: number(runtime.delivery_ratio, "M4.8Q delivery ratio"),
+      integratedGatePassed: exact(
+        runtime.integrated_runtime_gate_passed,
+        true,
+        "M4.8Q integrated gate",
+      ),
+      operatingTargetGatePassed: exact(
+        runtime.operating_target_gate_passed,
+        true,
+        "M4.8Q target gate",
+      ),
+    },
+    parity: {
+      precision: number(parity.risk_detection_precision, "M4.8Q parity precision"),
+      recall: number(parity.risk_detection_recall, "M4.8Q parity recall"),
+      meanIou: number(parity.matched_mean_iou, "M4.8Q parity IoU"),
+    },
+    acceptance: {
+      reviewReady: true,
+      independentQualityEvaluated: false,
+      semanticCandidateAccepted: false,
+    },
+    review: { cases },
+    method: method(raw.method),
+    limitations: array(raw.limitations, "M4.8Q limitations").map((item) =>
+      text(item, "M4.8Q limitation")
+    ),
+  };
+}
+
 export async function fetchM48TRiskQualityResult(
   resultId: string,
   {
@@ -313,7 +601,7 @@ export async function fetchM48TRiskQualityResult(
     signal,
   }: { fetcher?: LaboratoryFetch; signal?: AbortSignal } = {},
 ): Promise<M48TRiskQualityResult> {
-  if (!/^m48t-risk-quality-temporal-lab-[a-f0-9]{64}$/.test(resultId)) {
+  if (!/^(?:m48t-risk-quality-temporal-lab|m48q-native-risk-quality-lab)-[a-f0-9]{64}$/.test(resultId)) {
     throw new M48TContractError("M4.8T result identity недопустима.");
   }
   const response = await fetcher(`/api/v1/laboratory/m48t/risk-quality/results/${resultId}`, {
@@ -322,5 +610,9 @@ export async function fetchM48TRiskQualityResult(
     signal,
   });
   if (!response.ok) throw new M48TContractError(`M4.8T недоступен: HTTP ${response.status}.`);
-  return parseResult(await response.json(), resultId);
+  const payload: unknown = await response.json();
+  const raw = object(payload, "M4.8T/M4.8Q result");
+  return raw.schema_version === "missioncore.m48q-native-risk-quality-view/v1"
+    ? parseNativeResult(payload, resultId)
+    : parseLegacyResult(payload, resultId);
 }

apps/control-station/src/workspaces/laboratory/AdvancedLaboratoryResult.tsx

@@ -44,6 +44,7 @@ import { M4ReplayThreatResultView } from "./M4ReplayThreatResult";
 import { M47ReferenceGraphResultView } from "./M47ReferenceGraphResult";
 import { M48ObjectCentricQualityResultView } from "./M48ObjectCentricQualityResult";
 import { M48SmallStaticPassageRegressionResultView } from "./M48SmallStaticPassageRegressionResult";
+import { M48StaticOccupancyQualificationResultView } from "./M48StaticOccupancyQualificationResult";
 import { M48SFixedClassDetectorResultView } from "./M48SFixedClassDetectorResult";
 import { M48TRiskQualityResultView } from "./M48TRiskQualityResult";
 
@@ -94,6 +95,9 @@ export function AdvancedLaboratoryResult({
   if (workId === "m48-small-static-passage-regression" && results.m48SmallStatic) {
     return <M48SmallStaticPassageRegressionResultView rigLabel={rigLabel} result={results.m48SmallStatic} />;
   }
+  if (workId === "m48-static-occupancy-qualification" && results.m48StaticOccupancy) {
+    return <M48StaticOccupancyQualificationResultView rigLabel={rigLabel} result={results.m48StaticOccupancy} />;
+  }
   if (workId === "m48s-fixed-class-detector" && results.m48s) {
     return <M48SFixedClassDetectorResultView rigLabel={rigLabel} result={results.m48s} />;
   }

apps/control-station/src/workspaces/laboratory/M48StaticOccupancyQualificationEvidence.tsx

@@ -0,0 +1,91 @@
+import { useEffect, useMemo, useState } from "react";
+import { Icon } from "@nodedc/ui-react";
+
+import { fetchM47ReferenceGraphLab, type M47ReferenceGraphLabResult } from "../../core/laboratory/m47ReferenceGraph";
+import {
+  fetchM48StaticOccupancyCases,
+  type M48StaticOccupancyCase,
+  type M48StaticOccupancyQualificationResult,
+} from "../../core/laboratory/m48StaticOccupancyQualification";
+import {
+  M4ReplayThreatVisual,
+  type M4ReplayThreatReviewAnchor,
+} from "./M4ReplayThreatVisual";
+
+function message(error: unknown): string {
+  return error instanceof Error && error.message.trim()
+    ? error.message
+    : "Каноническое graph evidence M4.8R2 недоступно.";
+}
+
+export function M48StaticOccupancyQualificationEvidence({
+  result,
+}: {
+  result: M48StaticOccupancyQualificationResult;
+}) {
+  const [graph, setGraph] = useState<M47ReferenceGraphLabResult | null>(null);
+  const [cases, setCases] = useState<readonly M48StaticOccupancyCase[]>([]);
+  const [loading, setLoading] = useState(true);
+  const [error, setError] = useState<string | null>(null);
+
+  useEffect(() => {
+    const controller = new AbortController();
+    setLoading(true);
+    setError(null);
+    void Promise.all([
+      fetchM47ReferenceGraphLab({
+        resultId: result.referenceGraphLabResultId,
+        signal: controller.signal,
+      }),
+      fetchM48StaticOccupancyCases(result.resultId, { signal: controller.signal }),
+    ])
+      .then(([nextGraph, nextCases]) => {
+        if (controller.signal.aborted) return;
+        if (nextCases.some((item) => item.sequence < 1 || item.sequence > nextGraph.frames.expected)) {
+          throw new Error("M4.8R2 anchor вышел за immutable timeline Canonical Reference Graph.");
+        }
+        setGraph(nextGraph);
+        setCases(nextCases);
+      })
+      .catch((caught: unknown) => {
+        if (!controller.signal.aborted) setError(message(caught));
+      })
+      .finally(() => {
+        if (!controller.signal.aborted) setLoading(false);
+      });
+    return () => controller.abort();
+  }, [result.referenceGraphLabResultId, result.resultId]);
+
+  const reviewAnchors = useMemo<readonly M4ReplayThreatReviewAnchor[]>(() => (
+    cases.map((item) => ({
+      id: item.anchorId,
+      sourceSequence: item.sequence - 1,
+      extentXyxyNormalized: item.extentXyxy,
+      matchedAtThreshold: item.candidateQualified,
+    }))
+  ), [cases]);
+
+  if (loading) {
+    return (
+      <div className="l3-visual-audit__state" role="status">
+        <span className="busy-indicator" aria-hidden="true" />
+        <span>Открываем M4.7 graph и M4.8R2 static anchors</span>
+      </div>
+    );
+  }
+  if (error || !graph) {
+    return (
+      <div className="l3-visual-audit__state" role="alert">
+        <Icon name="alert" size={18} />
+        <span>{error ?? "Canonical Reference Graph не связан с M4.8R2."}</span>
+      </div>
+    );
+  }
+  return (
+    <M4ReplayThreatVisual
+      resultId={graph.visual.resultId}
+      semantic={{ resultId: graph.semantic.resultId, taxonomy: graph.semantic.taxonomy }}
+      reviewAnchors={reviewAnchors}
+    />
+  );
+}

apps/control-station/src/workspaces/laboratory/M48StaticOccupancyQualificationResult.tsx

@@ -0,0 +1,85 @@
+import {
+  LaboratoryEvidence,
+  LaboratoryResultSummary,
+  LaboratorySummary,
+  LaboratoryWorkTemplate,
+} from "../../components/laboratory/LaboratoryPresentation";
+import type { M48StaticOccupancyQualificationResult } from "../../core/laboratory/m48StaticOccupancyQualification";
+import { M48StaticOccupancyQualificationEvidence } from "./M48StaticOccupancyQualificationEvidence";
+
+function percent(value: number): string {
+  return `${(value * 100).toLocaleString("ru-RU", { maximumFractionDigits: 1 })}%`;
+}
+
+export function M48StaticOccupancyQualificationResultView({
+  rigLabel,
+  result,
+}: {
+  rigLabel: string;
+  result: M48StaticOccupancyQualificationResult;
+}) {
+  const nearReady = result.decision.criticalNearCandidateReadyForShadow;
+  const status = nearReady
+    ? "0–8 м: кандидат закрыл все assisted-якоря; готов к Worker shadow"
+    : "0–8 м: статическая occupancy ещё не закрыта";
+  return (
+    <LaboratoryWorkTemplate
+      summary={(
+        <LaboratorySummary
+          title="M4.8R2 · консервативная static occupancy"
+          description="RF-DETR не изменяется. Отдельный детерминированный прогон проверяет, удерживает ли current/rolling LiDAR низкие полусферы, столбы и другие безымянные ограничения, и оценивает уже вычисляемый CPU-признак low-step как additive occupied-only слой."
+          status={status}
+          statusTone={nearReady ? "success" : "warning"}
+          facts={[
+            { label: "Конфигурация", value: `${rigLabel} RIGHT · Canonical Reference Graph · VIDEO/CAMERA/3D/PLAN/SEMANTICS` },
+            { label: "Пайплайн", value: result.pipelineId },
+            { label: "Прогон", value: `${result.runLabel} · immutable ${result.resultId}` },
+            { label: "Нагрузка", value: "CPU-only geometry · 0 дополнительных detector inference" },
+            { label: "Authority", value: "REPLAY-SIMULATED · free-space/commands/actuation OFF" },
+          ]}
+          brief={{
+            question: "Не превратятся ли близкие полусферы, столбы и другие статические ограничения в пропуск только потому, что камера не знает их название?",
+            approach: `На ${result.metrics.operatorStaticAnchorCount} существующих operator-assisted static anchors принятую current/rolling occupancy сравнили с additive low-step evidence. Отдельно сохранены четыре канонических hemisphere-якоря кадров 1880/2584.`,
+            principalResult: `Принятый граф покрывает ${result.metrics.baselineQualifiedCount}/${result.metrics.operatorStaticAnchorCount}; additive кандидат — ${result.metrics.candidateQualifiedCount}/${result.metrics.operatorStaticAnchorCount}. В критической зоне 0–8 м: ${percent(result.metrics.criticalNearCandidateRecall)}.`,
+            limitation: "Это assisted diagnostic, а не independent truth. Кандидат пока не включён в Worker и может увеличить ложную занятость; требуются полный shadow-прогон, FPS и occupancy-volume gate.",
+          }}
+          method={{
+            completeness: "complete",
+            executionClass: "deterministic",
+            pipelineId: result.pipelineId,
+            components: [
+              { kind: "source", name: result.referenceGraphLabResultId, version: "accepted M4.7", role: "immutable current/rolling occupied/unknown + threat graph", identitySha256: result.referenceGraphLabResultId.split("-").at(-1) ?? null },
+              { kind: "source", name: result.smallStaticResultId, version: "M4.8R1 assisted seed", role: "static avoidance anchors · not independent truth", identitySha256: result.smallStaticResultId.split("-").at(-1) ?? null },
+              { kind: "algorithm", name: "low-step occupied-only candidate", version: "v1", role: "additive CPU geometry; never clearing", identitySha256: result.resultId.split("-").at(-1) ?? null },
+            ],
+          }}
+        />
+      )}
+      evidence={(
+        <LaboratoryEvidence eyebrow="M4.8R2 VISUAL EVIDENCE · CANONICAL REFERENCE GRAPH" title="Те же CAMERA/3D/PLAN, 11 static anchors и неизменённый M4.7 timeline" kind="recorded-replay" resizable>
+          <M48StaticOccupancyQualificationEvidence result={result} />
+        </LaboratoryEvidence>
+      )}
+      result={(
+        <LaboratoryResultSummary
+          title="Что дал прогон: локализован лёгкий геометрический слой для близких препятствий"
+          status={status}
+          statusTone={nearReady ? "success" : "warning"}
+          metrics={[
+            { label: "Current graph", value: `${result.metrics.baselineQualifiedCount}/${result.metrics.operatorStaticAnchorCount}`, hint: `${percent(result.metrics.criticalNearBaselineRecall)} в 0–8 м` },
+            { label: "+ low-step candidate", value: `${result.metrics.candidateQualifiedCount}/${result.metrics.operatorStaticAnchorCount}`, hint: `${percent(result.metrics.criticalNearCandidateRecall)} в 0–8 м` },
+            { label: "8–12 м", value: percent(result.metrics.approachCandidateRecall), hint: `${result.metrics.approachAnchorCount} assisted anchors · ещё не gate` },
+            { label: "False free", value: result.metrics.falseFreeCount.toLocaleString("ru-RU"), hint: `${result.metrics.canonicalEngineeringAnchorCount}/${result.metrics.canonicalEngineeringAnchorCount} canonical anchors retained` },
+          ]}
+          conclusion={{
+            proved: `На замороженном assisted seed additive low-step evidence поднял покрытие близких static anchors до ${percent(result.metrics.criticalNearCandidateRecall)} без дополнительной нейросети и без единого free-space утверждения.`,
+            notProved: "Не доказаны independent precision/recall, приемлемый рост консервативной occupancy, realtime Worker FPS после интеграции, физический clearance и collision safety.",
+            decision: nearReady
+              ? "Интегрировать low-step только как occupied/unknown Worker shadow. Затем прогнать все 4 489 кадров и принять по FPS, росту компонентов, отсутствию capacity drops и повторному static-anchor gate."
+              : "Не интегрировать в Worker до исправления близких пропусков.",
+          }}
+        />
+      )}
+    />
+  );
+}

apps/control-station/src/workspaces/laboratory/M48TRiskQualityResult.tsx

@@ -4,7 +4,11 @@ import {
   LaboratorySummary,
   LaboratoryWorkTemplate,
 } from "../../components/laboratory/LaboratoryPresentation";
-import type { M48TRiskQualityResult } from "../../core/laboratory/m48tRiskQuality";
+import type {
+  M48QNativeRiskQualityResult,
+  M48TLegacyRiskQualityResult,
+  M48TRiskQualityResult,
+} from "../../core/laboratory/m48tRiskQuality";
 import { M48TRiskQualityVisual } from "./M48TRiskQualityVisual";
 
 function percent(value: number, digits = 1): string {
@@ -21,6 +25,19 @@ export function M48TRiskQualityResultView({
 }: {
   rigLabel: string;
   result: M48TRiskQualityResult;
+}) {
+  if (result.variant === "native-risk-review") {
+    return <M48QNativeRiskQualityResultView rigLabel={rigLabel} result={result} />;
+  }
+  return <M48TLegacyRiskQualityResultView rigLabel={rigLabel} result={result} />;
+}
+
+function M48TLegacyRiskQualityResultView({
+  rigLabel,
+  result,
+}: {
+  rigLabel: string;
+  result: M48TLegacyRiskQualityResult;
 }) {
   return (
     <LaboratoryWorkTemplate
@@ -77,3 +94,69 @@ export function M48TRiskQualityResultView({
     />
   );
 }
+
+function M48QNativeRiskQualityResultView({
+  rigLabel,
+  result,
+}: {
+  rigLabel: string;
+  result: M48QNativeRiskQualityResult;
+}) {
+  const classes = Object.entries(result.selection.classCounts)
+    .map(([name, count]) => `${name} ${count}`)
+    .join(" · ");
+  return (
+    <LaboratoryWorkTemplate
+      summary={(
+        <LaboratorySummary
+          title="M4.8Q · native raw-fisheye risk review"
+          description="Нативный RF-DETR прогнан внутри полного reference graph прямо на исходном KB4 raster 800×600: без rectification, warp, resize и обратного преобразования. Из immutable frame ledger детерминированно отобраны реальные risk-кейсы для операторской проверки в существующем M4.8 image-case instrument."
+          status="Runtime принят · 24 native cases готовы · quality ещё не adjudicated"
+          statusTone="success"
+          facts={[
+            { label: "Source", value: `${rigLabel} · ${result.source.frameCount.toLocaleString("ru-RU")} raw frames · 800×600` },
+            { label: "Candidate", value: `${result.candidate.modelId} · score ≥ ${decimal(result.candidate.minimumScore, 2)}` },
+            { label: "Image path", value: "RAW KB4 → fused GPU graph · geometric resampling NO" },
+            { label: "Authority", value: "SHADOW ONLY · independent quality NO · production NO" },
+          ]}
+          brief={{
+            question: "Работает ли нативная risk-классификация на нашей исходной fisheye-картинке в realtime envelope, и какие реальные кадры надо проверить человеком?",
+            approach: `Полный ${result.source.frameCount.toLocaleString("ru-RU")}-кадровый native graph оставлен неизменным. Повторной инференс-сессии для лабы нет: 24 кадра выбраны из его hash-bound ledger по person, animal, light-road-user, vehicle, low-confidence, fisheye-edge и расхождениям с диагностической legacy 704 веткой.`,
+            principalResult: `${decimal(result.execution.effectiveWorldStateFps, 3)} FPS при detector p95 ${decimal(result.execution.detectorTotalP95Ms, 2)} ms и world-state p95 ${decimal(result.execution.worldStateCompletionP95Ms, 2)} ms. В review pack реально попали ${classes}.`,
+            limitation: "Это диагностическая выборка маршрута без независимой разметки. Наличие бокса и класса можно осмотреть, но precision/recall и корректность каждого класса этой фазой ещё не доказаны.",
+          }}
+          method={result.method}
+        />
+      )}
+      evidence={(
+        <LaboratoryEvidence
+          eyebrow="M4.8Q VISUAL EVIDENCE · NATIVE RAW KB4"
+          title="24 исходных fisheye-кадра с отключаемым client-side overlay"
+          kind="diagnostic-model"
+          resizable
+        >
+          <M48TRiskQualityVisual result={result} />
+        </LaboratoryEvidence>
+      )}
+      result={(
+        <LaboratoryResultSummary
+          title="Native runtime закрыт; следующий честный шаг — adjudication этих кейсов"
+          status="Review-ready · quality-not-adjudicated"
+          statusTone="success"
+          metrics={[
+            { label: "Full graph", value: `${decimal(result.execution.effectiveWorldStateFps, 3)} FPS`, hint: `delivery ${percent(result.runtime.deliveryRatio, 2)} · 4 489/4 489` },
+            { label: "Detector / world-state p95", value: `${decimal(result.execution.detectorTotalP95Ms, 2)} / ${decimal(result.execution.worldStateCompletionP95Ms, 2)} ms`, hint: "один native pass · additional inference 0" },
+            { label: "GPU / VRAM peak", value: `${decimal(result.execution.gpuUtilizationP95Percent, 1)}% / ${decimal(result.execution.gpuMemoryMaximumMib / 1024, 2)} GiB`, hint: "Worker 006 · RTX 4090 envelope" },
+            { label: "Native parity", value: `${percent(result.parity.precision, 2)} / ${percent(result.parity.recall, 2)}`, hint: `precision / recall · mean IoU ${percent(result.parity.meanIou, 2)}` },
+            { label: "Review pack", value: `${result.selection.caseCount}/24 cases`, hint: "8 diagnostic buckets · raw 800×600" },
+          ]}
+          conclusion={{
+            proved: `Полный reference graph доставил все ${result.source.frameCount.toLocaleString("ru-RU")} world states на ${decimal(result.execution.effectiveWorldStateFps, 3)} FPS. Детектор использовал ровно один native 800×600 KB4 pass без геометрического resampling. Hash-bound review содержит person, dog, bicycle, skateboard, car и truck; боксы рисуются поверх чистого кадра и отключаются кнопкой.`,
+            notProved: "Не доказаны route-domain precision/recall, истинность 24 классов и боксов, child/adult, поведение объектов, физическая track identity и безопасность навигации. Legacy 704 count delta остаётся только диагностикой, потому что старая ветка растягивала 4:3 raster.",
+            decision: "Не добавлять второй detector и не менять realtime graph. Использовать эти 24 кейса как вход существующего M4.8 review/correction workflow; только после независимой adjudication считать route-domain semantic quality.",
+          }}
+        />
+      )}
+    />
+  );
+}

apps/control-station/src/workspaces/laboratory/M48TRiskQualityVisual.tsx

@@ -1,18 +1,35 @@
-import { useState } from "react";
+import { useMemo, useState } from "react";
 import { Icon, IconButton } from "@nodedc/ui-react";
 
 import { LaboratoryEvidenceViewer } from "../../components/laboratory/LaboratoryEvidenceViewer";
-import type { M48TRiskQualityResult } from "../../core/laboratory/m48tRiskQuality";
+import { RecordedEvidenceImageScene } from "../../components/laboratory/RecordedEvidenceImageScene";
+import type {
+  RecordedEvidenceBox,
+  RecordedEvidenceBoxTone,
+} from "../../components/laboratory/RecordedEvidenceBoxOverlay";
+import type {
+  M48QNativeRiskQualityResult,
+  M48QRiskFamily,
+  M48TLegacyRiskQualityResult,
+  M48TRiskQualityResult,
+} from "../../core/laboratory/m48tRiskQuality";
 
-export function M48TRiskQualityVisual({ result }: { result: M48TRiskQualityResult }) {
+function navigateIndex(current: number, offset: -1 | 1, length: number): number {
+  return (current + offset + length) % length;
+}
+
+function familyTone(family: M48QRiskFamily): RecordedEvidenceBoxTone {
+  if (family === "person" || family === "animal") return "danger";
+  if (family === "light-road-user") return "warning";
+  return "accent";
+}
+
+function LegacyVisual({ result }: { result: M48TLegacyRiskQualityResult }) {
   const [index, setIndex] = useState(0);
   const [expanded, setExpanded] = useState(false);
   const item = result.review.cases[index] ?? null;
-  const navigate = (offset: -1 | 1) => {
-    setIndex((current) => (
-      current + offset + result.review.cases.length
-    ) % result.review.cases.length);
-  };
+  const navigate = (offset: -1 | 1) =>
+    setIndex((current) => navigateIndex(current, offset, result.review.cases.length));
 
   return (
     <div className="l3-visual-audit">
@@ -61,3 +78,85 @@ export function M48TRiskQualityVisual({ result }: { result: M48TRiskQualityResul
     </div>
   );
 }
+
+function NativeVisual({ result }: { result: M48QNativeRiskQualityResult }) {
+  const [index, setIndex] = useState(0);
+  const [expanded, setExpanded] = useState(false);
+  const [boxesVisible, setBoxesVisible] = useState(true);
+  const item = result.review.cases[index] ?? null;
+  const boxes = useMemo<readonly RecordedEvidenceBox[]>(() => {
+    if (!item || !boxesVisible) return [];
+    return item.proposals.map((proposal) => ({
+      boxXyxy: proposal.boxXyxy,
+      label: `${proposal.className} · ${proposal.score.toFixed(2)}`,
+      tone: familyTone(proposal.riskFamily),
+    }));
+  }, [boxesVisible, item]);
+  const navigate = (offset: -1 | 1) =>
+    setIndex((current) => navigateIndex(current, offset, result.review.cases.length));
+
+  return (
+    <div className="l3-visual-audit">
+      <LaboratoryEvidenceViewer
+        label="M4.8Q native raw-fisheye risk review"
+        mode="native"
+        modes={[{ value: "native", label: "NATIVE RF-DETR" }]}
+        expanded={expanded}
+        onModeChange={() => undefined}
+        onExpandedChange={setExpanded}
+        actions={(
+          <div className="l3-visual-audit__pagination">
+            <IconButton label="Предыдущий M4.8Q review case" onClick={() => navigate(-1)}>
+              <Icon name="chevron-left" size={16} />
+            </IconButton>
+            <IconButton label="Следующий M4.8Q review case" onClick={() => navigate(1)}>
+              <Icon name="chevron-right" size={16} />
+            </IconButton>
+          </div>
+        )}
+        trailingActions={(
+          <IconButton
+            label={boxesVisible ? "Скрыть native RF-DETR боксы" : "Показать native RF-DETR боксы"}
+            onClick={() => setBoxesVisible((visible) => !visible)}
+          >
+            <Icon name={boxesVisible ? "eye-off" : "eye"} size={16} />
+          </IconButton>
+        )}
+        overlay={item ? (
+          <div className="l3-visual-audit__overlay">
+            <div>
+              <span>RAVNOVES00 · raw KB4 800×600 · resampling NO</span>
+              <strong>
+                case {index + 1}/{result.review.cases.length} · frame {item.sequence} · {item.proposals.length} native boxes
+              </strong>
+              <small>
+                {item.selectionBuckets.join(" · ")} · native/legacy {item.nativeDetectionCount}/{item.legacyDetectionCount} (diagnostic only)
+              </small>
+            </div>
+          </div>
+        ) : null}
+      >
+        {item ? (
+          <RecordedEvidenceImageScene
+            src={item.imageUrl}
+            imageWidth={item.width}
+            imageHeight={item.height}
+            boxes={boxes}
+            ariaLabel={`M4.8Q frame ${item.sequence}: ${boxes.length} visible native risk boxes`}
+          />
+        ) : (
+          <div className="l3-visual-audit__state" role="alert">
+            <Icon name="alert" size={18} />
+            M4.8Q native visual evidence недоступно.
+          </div>
+        )}
+      </LaboratoryEvidenceViewer>
+    </div>
+  );
+}
+
+export function M48TRiskQualityVisual({ result }: { result: M48TRiskQualityResult }) {
+  return result.variant === "native-risk-review"
+    ? <NativeVisual result={result} />
+    : <LegacyVisual result={result} />;
+}

apps/control-station/src/workspaces/laboratory/laboratoryArchiveProfiles.ts

@@ -77,6 +77,13 @@ const KNOWN_WORKS: Readonly<Record<Exclude<LaboratoryWorkId, `session:${string}`
     experimentName: "M4.8 · small static passage regression",
     variantName: "M4.8R1 · Worker 006 small-static assisted baseline",
   },
+  "m48-static-occupancy-qualification": {
+    profileId: "rig-dual-evidence-virtual-corridor-v1",
+    profileName: (rigLabel) => `${rig(rigLabel)} RIGHT · Canonical Reference Graph`,
+    experimentId: "m48-static-occupancy-qualification",
+    experimentName: "M4.8 · conservative static occupancy qualification",
+    variantName: "M4.8R2 · current/rolling + low-step occupied-only candidate",
+  },
   "m48s-fixed-class-detector": {
     profileId: "rig-ravnoves-perception-gate-v1",
     profileName: (rigLabel) => `${rig(rigLabel)} RIGHT · RAVNOVES00 perception gate`,
@@ -86,10 +93,10 @@ const KNOWN_WORKS: Readonly<Record<Exclude<LaboratoryWorkId, `session:${string}`
   },
   "m48t-risk-quality-temporal": {
     profileId: "rig-ravnoves-perception-gate-v1",
-    profileName: (rigLabel) => `${rig(rigLabel)} RIGHT · COCO quality + bounded temporal identity`,
+    profileName: (rigLabel) => `${rig(rigLabel)} RIGHT · Native raw-fisheye perception gate`,
     experimentId: "m48t-risk-quality-temporal",
-    experimentName: "RF-DETR independent semantic quality and temporal identity",
-    variantName: "M4.8T · COCO val2017 truth + RAVNOVES00 temporal shadow",
+    experimentName: "RF-DETR native risk review and temporal identity",
+    variantName: "M4.8Q · native raw KB4 review · quality not adjudicated",
   },
   "m47-reference-graph-shadow": {
     profileId: "rig-dual-evidence-virtual-corridor-v1",

apps/control-station/src/workspaces/laboratory/useAdvancedLaboratoryCatalog.ts

@@ -21,6 +21,7 @@ function mergeResults(
     m47Graph: next.m47Graph ?? current.m47Graph,
     m48: next.m48 ?? current.m48,
     m48SmallStatic: next.m48SmallStatic ?? current.m48SmallStatic,
+    m48StaticOccupancy: next.m48StaticOccupancy ?? current.m48StaticOccupancy,
     m48s: next.m48s ?? current.m48s,
     m48t: next.m48t ?? current.m48t,
     m4Threat: next.m4Threat ?? current.m4Threat,
@@ -120,6 +121,7 @@ export function useAdvancedLaboratoryCatalog({
         "m47-reference-graph-shadow",
         "m48-object-centric-quality",
         "m48-small-static-passage-regression",
+        "m48-static-occupancy-qualification",
       ].includes(selectedWorkId)
       && !indexedResultId
     ) return;

apps/control-station/test/m48tRiskQuality.test.mjs

@@ -0,0 +1,172 @@
+import assert from "node:assert/strict";
+import { after, before, test } from "node:test";
+import { readFile } from "node:fs/promises";
+import { createServer } from "vite";
+
+let server;
+let fetchM48TRiskQualityResult;
+
+const resultId = `m48q-native-risk-quality-lab-${"a".repeat(64)}`;
+
+before(async () => {
+  server = await createServer({
+    appType: "custom",
+    logLevel: "silent",
+    server: { middlewareMode: true },
+  });
+  ({ fetchM48TRiskQualityResult } = await server.ssrLoadModule(
+    "/src/core/laboratory/m48tRiskQuality.ts",
+  ));
+});
+
+after(async () => server?.close());
+
+function response(value) {
+  return { ok: true, status: 200, json: async () => value };
+}
+
+function payload() {
+  return {
+    schema_version: "missioncore.m48q-native-risk-quality-view/v1",
+    variant: "native-risk-review",
+    result_id: resultId,
+    created_at_utc: "2026-08-26T10:00:00Z",
+    status: "complete-review-ready-quality-not-adjudicated",
+    access: "read-only",
+    ground_truth: false,
+    source: {
+      source_id: "RAVNOVES00",
+      frame_count: 4489,
+      raster_width: 800,
+      raster_height: 600,
+      geometric_resampling: false,
+      rectification: false,
+      warp: false,
+    },
+    configuration: {
+      candidate: {
+        provider_id: "triton-rf-detr-large-coco-native-kb4-risk-fp16-shadow/v0",
+        model_id: "rf_detr_large_native_kb4:1",
+        preprocess_id: "raw-kb4-uint8-fused-mask-rgb-pad8-imagenet-trt/v0",
+        minimum_score: 0.25,
+      },
+    },
+    method: {
+      schema_version: "missioncore.laboratory-method/v1",
+      completeness: "complete",
+      execution_class: "hybrid",
+      pipeline_id: "m48q-native-raw-fisheye-risk-case-review/v1",
+      components: [{
+        kind: "model",
+        name: "RF-DETR-L native KB4 TensorRT",
+        version: "rf_detr_large_native_kb4:1",
+        role: "risk proposals",
+        identity_sha256: "b".repeat(64),
+      }],
+    },
+    execution: {
+      effective_world_state_fps: 11.84338,
+      world_state_completion_p95_ms: 47.940779,
+      detector_total_p95_ms: 21.19895,
+      gpu_utilization_p95_percent: 53,
+      gpu_memory_used_maximum_mib: 9718,
+      additional_inference_passes: 0,
+    },
+    metrics: {
+      selection: {
+        case_count: 24,
+        minimum_sequence_separation: 12,
+        selected_bucket_coverage: { person: 22, animal: 3 },
+        selected_class_counts: { person: 44, dog: 3 },
+      },
+      runtime: {
+        delivery_ratio: 1,
+        integrated_runtime_gate_passed: true,
+        operating_target_gate_passed: true,
+      },
+      native_tensor_parity: {
+        risk_detection_precision: 0.9887,
+        risk_detection_recall: 0.9831,
+        matched_mean_iou: 0.9882,
+      },
+    },
+    acceptance: {
+      review_ready: true,
+      integrated_runtime_gate_passed: true,
+      independent_quality_evaluated: false,
+      semantic_candidate_accepted: false,
+    },
+    review: {
+      source_raster: { width: 800, height: 600 },
+      overlay: { client_rendered: true, toggleable: true },
+      cases: Array.from({ length: 24 }, (_, index) => {
+        const caseId = String(index * 20 + 12).padStart(6, "0");
+        return {
+          case_id: caseId,
+          sequence: Number(caseId),
+          frame_id: `frame-${caseId}`,
+          evidence_time_ns: 35_000_000_000 + index * 1_000_000,
+          image_url: `/review/${caseId}.jpg`,
+          media_type: "image/jpeg",
+          width: 800,
+          height: 600,
+          byte_length: 1000 + index,
+          sha256: String(index.toString(16)).padStart(64, "0"),
+          geometric_resampling: false,
+          selection_buckets: [index % 2 ? "person" : "animal"],
+          comparison: {
+            native_detection_count: 1,
+            legacy_704_detection_count: 1,
+            matched_detection_count_iou_at_least_0_5: 1,
+          },
+          proposals: [{
+            proposal_id: `proposal-${index}-0`,
+            class_name: index % 2 ? "person" : "dog",
+            risk_family: index % 2 ? "person" : "animal",
+            score: 0.75,
+            box_xyxy: [10, 20, 100, 200],
+          }],
+        };
+      }),
+    },
+    limitations: ["No independent route truth."],
+  };
+}
+
+test("M4.8Q parser accepts only the native 800x600 no-resampling review contract", async () => {
+  const result = await fetchM48TRiskQualityResult(resultId, {
+    fetcher: async () => response(payload()),
+  });
+
+  assert.equal(result.variant, "native-risk-review");
+  assert.equal(result.review.cases.length, 24);
+  assert.equal(result.review.cases[0].width, 800);
+  assert.equal(result.review.cases[0].proposals[0].className, "dog");
+  assert.equal(result.execution.additionalInferencePasses, 0);
+  assert.equal(result.acceptance.independentQualityEvaluated, false);
+});
+
+test("M4.8Q parser fails closed if raw-fisheye geometry is resampled", async () => {
+  const invalid = payload();
+  invalid.source.geometric_resampling = true;
+
+  await assert.rejects(
+    fetchM48TRiskQualityResult(resultId, {
+      fetcher: async () => response(invalid),
+    }),
+    /source resampling/,
+  );
+});
+
+test("M4.8Q reuses the canonical image scene and viewer overlay toggle", async () => {
+  const source = await readFile(
+    new URL("../src/workspaces/laboratory/M48TRiskQualityVisual.tsx", import.meta.url),
+    "utf8",
+  );
+
+  assert.match(source, /<LaboratoryEvidenceViewer/);
+  assert.match(source, /<RecordedEvidenceImageScene/);
+  assert.match(source, /name=\{boxesVisible \? "eye-off" : "eye"\}/);
+  assert.match(source, /raw KB4 800×600 · resampling NO/);
+  assert.doesNotMatch(source, /<canvas/);
+});

config/laboratories/m48-static-occupancy-qualification.json

@@ -0,0 +1,10 @@
+{
+  "schema_version": "missioncore.laboratory-evidence-definition/v1",
+  "work_id": "m48-static-occupancy-qualification",
+  "evidence": {
+    "runtime_relative_root": "m48/static-occupancy-qualification-results",
+    "result_id_prefix": "m48-static-occupancy-qualification",
+    "document_name": "manifest.json",
+    "schema_version": "missioncore.m48-static-occupancy-qualification-result/v1"
+  }
+}

config/laboratories/m48t-risk-quality-temporal.json

@@ -1,10 +1,20 @@
 {
-  "schema_version": "missioncore.laboratory-evidence-definition/v1",
+  "schema_version": "missioncore.laboratory-evidence-definition/v2",
   "work_id": "m48t-risk-quality-temporal",
-  "evidence": {
-    "runtime_relative_root": "m48t-risk-quality/lab-results",
-    "result_id_prefix": "m48t-risk-quality-temporal-lab",
-    "document_name": "manifest.json",
-    "schema_version": "missioncore.m48t-risk-quality-temporal-lab/v1"
-  }
+  "evidence_lifecycle": [
+    {
+      "phase": "legacy-quality",
+      "runtime_relative_root": "m48t-risk-quality/lab-results",
+      "result_id_prefix": "m48t-risk-quality-temporal-lab",
+      "document_name": "manifest.json",
+      "schema_version": "missioncore.m48t-risk-quality-temporal-lab/v1"
+    },
+    {
+      "phase": "result",
+      "runtime_relative_root": "m48t-risk-quality/native-lab-results",
+      "result_id_prefix": "m48q-native-risk-quality-lab",
+      "document_name": "manifest.json",
+      "schema_version": "missioncore.m48q-native-risk-quality-lab/v1"
+    }
+  ]
 }

config/laboratory-execution.json

@@ -1,6 +1,26 @@
 {
   "schema_version": "missioncore.laboratory-execution-registry/v1",
   "definitions": [
+    {
+      "work_id": "m48-static-occupancy-qualification",
+      "lifecycle": "canonical",
+      "isolation": "core-adapter",
+      "adapter_id": "canonical.m48-static-occupancy-qualification/v1",
+      "input_roles": [
+        "repository_root",
+        "profile_path",
+        "m47_lab_root",
+        "graph_result_root",
+        "small_static_result_root"
+      ],
+      "contracts": {
+        "source": "missioncore.m48-static-occupancy-source-set/v1",
+        "provider": "missioncore.m48-additive-low-step-occupancy/v1",
+        "graph": "missioncore.m48-static-occupancy-case/v1",
+        "run": "missioncore.laboratory-run/v1",
+        "evidence": "missioncore.m48-static-occupancy-qualification-result/v1"
+      }
+    },
     {
       "work_id": "m48-small-static-passage-regression",
       "lifecycle": "canonical",

config/laboratory-value-review.json

@@ -1,6 +1,6 @@
 {
   "schema_version": "missioncore.laboratory-value-review-registry/v1",
-  "reviewed_at_utc": "2026-08-25T11:06:28Z",
+  "reviewed_at_utc": "2026-08-26T08:34:34Z",
   "entries": [
     {
       "catalog_id": "e28-local-surface",
@@ -247,6 +247,13 @@
       "lifecycle": "current",
       "visual_evidence": "available"
     },
+    {
+      "catalog_id": "m48-static-occupancy-qualification",
+      "evidence_id": "m48-static-occupancy-qualification-568024554cff011332ff19ca4739f70555a6232c0607dec2a71be6db408ea69a",
+      "signal": "progress",
+      "lifecycle": "current",
+      "visual_evidence": "available"
+    },
     {
       "catalog_id": "m48s-fixed-class-detector",
       "evidence_id": "m48s-fixed-class-detector-lab-4a901d811f53734540337f8d1f2c01666539aa0a9b7786f26d4f1f2e08cc858a",
@@ -256,7 +263,7 @@
     },
     {
       "catalog_id": "m48t-risk-quality-temporal",
-      "evidence_id": "m48t-risk-quality-temporal-lab-ed5355fe0adb9b18942d75aff2362d79190b9e864f070ebe7a1c15fccbc0fbfb",
+      "evidence_id": "m48q-native-risk-quality-lab-e8961d4db8ffb751503b9646bc8eeebec6c80c948ce2f5b4fa5b89c471e673c1",
       "signal": "progress",
       "lifecycle": "current",
       "visual_evidence": "available"

config/perception/m48-static-occupancy-qualification-v1.json

@@ -0,0 +1,56 @@
+{
+  "schema_version": "missioncore.m48-static-occupancy-qualification-profile/v1",
+  "profile_id": "m48-conservative-static-occupancy/v1",
+  "pipeline_id": "m4-current-rolling-plus-step-static-occupancy/v1",
+  "experiment_id": "m48-static-occupancy-qualification/v1",
+  "human_lab_id": "M4.8",
+  "run_label": "M4.8R2",
+  "source": {
+    "source_id": "RAVNOVES00",
+    "source_session_id": "20260720T065719Z_viewer_live",
+    "m47_lab_result_id": "m47-reference-graph-lab-49678f0a7c628c7e991af0964fa57d005baa027d2d1eea19f38bbfe27ed39ce5",
+    "m47_graph_result_id": "m47-reference-graph-5f6a851cd655c7cf07c3025dacadbc188018b0afa97eda3a08802266e12da87d",
+    "m47_graph_frames_sha256": "d2cd53f8cff555410959600a79eb9a101aad4a8009ba87bdd0f3c5f122948071",
+    "small_static_result_id": "m48-small-static-passage-regression-3e3a2001f87fd3adcb736de52a65e42515044d83faa3515f892705b40915c084",
+    "small_static_anchors_sha256": "6a317aa75dde8204d5574a56166bebc9347e8797934dbc82f076a0abfdfaa95a"
+  },
+  "selection": {
+    "motion": "static",
+    "requires_avoidance_or_clearance": true,
+    "canonical_engineering_sequences": [1880, 2584],
+    "independent_truth": false
+  },
+  "distance_bands_m": {
+    "critical_near": [0.0, 8.0],
+    "approach": [8.0, 12.0]
+  },
+  "candidate": {
+    "point_sources": ["local-surface-occupied", "local-surface-step-candidate"],
+    "minimum_points": 2,
+    "minimum_voxels": 1,
+    "voxel_size_m": 0.35,
+    "depth_cluster_minimum_gap_m": 0.65,
+    "depth_cluster_gap_fraction": 0.08,
+    "spatial_cluster_radius_m": 0.75
+  },
+  "acceptance": {
+    "minimum_critical_near_candidate_recall": 1.0,
+    "minimum_approach_candidate_recall": 0.95,
+    "minimum_canonical_engineering_recall": 1.0,
+    "maximum_false_free_count": 0
+  },
+  "policy": {
+    "absence_of_points_means_free": false,
+    "absence_of_camera_detection_means_free": false,
+    "step_candidate_can_only_add_occupied_or_unknown": true,
+    "semantic_class_used": false,
+    "planner_authoritative_free_space_claimed": false
+  },
+  "authority": {
+    "mode": "replay-simulated",
+    "physical_live": false,
+    "commands_enabled": false,
+    "actuation_allowed": false,
+    "navigation_or_safety_accepted": false
+  }
+}

config/perception/m48q-native-risk-case-mining-v1.json

@@ -0,0 +1,58 @@
+{
+  "schema_version": "missioncore.m48q-native-risk-case-mining-profile/v1",
+  "profile_id": "m48q-ravnoves00-native-raw-kb4-risk-review/v1",
+  "question": "Which real RAVNOVES00 raw-fisheye frames expose the native RF-DETR risk semantics that require operator review before independent route truth exists?",
+  "source": {
+    "source_id": "RAVNOVES00",
+    "frame_count": 4489,
+    "raster_width": 800,
+    "raster_height": 600,
+    "video_sha256": "cadd1696ff000904eb78633a0a8418104b8024f178b91f3421789021ccb160e8",
+    "geometric_resampling": false,
+    "rectification": false,
+    "warp": false
+  },
+  "candidate": {
+    "provider_id": "triton-rf-detr-large-coco-native-kb4-risk-fp16-shadow/v0",
+    "model_id": "rf_detr_large_native_kb4:1",
+    "preprocess_id": "raw-kb4-uint8-fused-mask-rgb-pad8-imagenet-trt/v0",
+    "engine_sha256": "b8a40b3580edff001ec9680de68707242294ff590ab296000fae371f1083f695",
+    "minimum_score": 0.25
+  },
+  "risk_families": {
+    "person": ["person"],
+    "animal": ["bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe"],
+    "light-road-user": ["bicycle", "motorcycle", "skateboard"],
+    "vehicle": ["car", "bus", "truck"]
+  },
+  "selection": {
+    "case_count": 24,
+    "minimum_sequence_separation": 12,
+    "low_confidence_maximum_score": 0.4,
+    "fisheye_edge_margin_fraction": 0.12,
+    "bucket_quotas": {
+      "person": 3,
+      "animal": 3,
+      "light-road-user": 3,
+      "vehicle": 3,
+      "low-confidence": 3,
+      "fisheye-edge": 3,
+      "native-fewer-than-legacy": 3,
+      "native-more-than-legacy": 3
+    }
+  },
+  "scope": {
+    "quality_evaluated": false,
+    "ground_truth": false,
+    "candidate_accepted": false,
+    "production_accepted": false,
+    "purpose": "bounded-native-risk-case-review"
+  },
+  "authority": {
+    "ground_truth": false,
+    "candidate_accepted": false,
+    "commands_enabled": false,
+    "actuation_allowed": false,
+    "navigation_or_safety_accepted": false
+  }
+}

docs/13_LIDAR_WORKER_PRODUCT_AND_ROADMAP.md

@@ -912,6 +912,17 @@ authority.
 Exit: local collision-space quality and deadline gates pass in replay and
 shadow. This still does not authorize control.
 
+M4.8R2 now supplies the bounded pre-shadow qualification for the first item.
+On eleven operator-assisted static passage anchors, the accepted current/rolling
+graph covers `6/11`, while the additive sealed low-step signal covers `10/11`;
+the critical `0–8 m` subset is `9/9`, four canonical engineering anchors remain
+matched and false-free count is zero. The item remains unchecked because this
+is not independent truth and the candidate is not yet part of the Worker
+pipeline. Its next gate is a full `4,489`-frame occupied-only Worker 006 shadow
+with FPS, latency, occupancy growth, component-count and capacity-drop bounds.
+Dynamic decay, Nav2 publication and planner-authoritative free space remain
+separate later work.
+
 ### L6 — alternative odometry/mapping
 
 This stage starts only when a source supplies unregistered sensor scans. Add

docs/17_PRODUCT_UI_AND_LAB_PRESENTATION_CANON.md

@@ -179,6 +179,13 @@ only on the annotated frame unless a separately evidenced and reviewable
 tracking result exists; ordinary model proposals and graph layers continue on
 their own full recorded timeline.
 
+M4.8R2 is the canonical static-occupancy example of this rule. Its report and
+eleven typed anchors bind to the accepted M4.7 LAB identity, use the same
+`VIDEO/CAMERA/3D/PLAN/SEMANTICS` timeline and add no renderer or transport. A
+qualified anchor means the additive occupied-only candidate has LiDAR support
+inside that exact reviewed camera extent; it does not turn the extent into a 3D
+collider or grant clearance, free-space, navigation or safety authority.
+
 A third perception instrument is a product-surface change. It requires explicit
 product-owner agreement before implementation and cannot be introduced by a LAB
 adapter, result component or experiment configuration.

docs/22_MILESTONE_4_OBJECT_CENTRIC_RECORDED_REALTIME_CV.md

@@ -1445,6 +1445,65 @@ configuration, dataset release, metrics and ONNX identity; only then is a
 candidate loaded through the existing Triton seam and measured by a new
 append-only M4.8R run plus an independent validation gate.
 
+### 2026-08-26 — M4.8Q native raw-fisheye risk review ready
+
+The terminal phase of the existing `m48t-risk-quality-temporal` work is now the
+content-addressed M4.8Q result
+`m48q-native-risk-quality-lab-e8961d4db8ffb751503b9646bc8eeebec6c80c948ce2f5b4fa5b89c471e673c1`.
+It replaces neither the historical M4.8T evidence nor either admitted M4 viewer.
+The result projects `24` deterministic diagnostic cases into the existing M4.8
+image-case review instrument, with source-pixel boxes rendered by the client and
+an explicit clean-image toggle. The JPEG review derivatives retain the exact
+`800×600` raster geometry; rectification, warp and geometric resampling are all
+false. Boxes are not baked into the images.
+
+Worker 006 selected the cases from the immutable full native reference-graph
+ledger without another inference pass. The selection covers person, animal,
+light-road-user, vehicle, low-confidence, fisheye-edge and both directions of
+native-versus-legacy count divergence, with at least 12 source frames between
+selected cases. The source graph delivered all `4,489/4,489` frames at
+`11.84338 FPS`; detector p95 was `21.19895 ms`, world-state completion p95 was
+`47.940779 ms`, GPU utilization p95 was `53%`, and maximum used GPU memory was
+`9,718 MiB`. The isolated case-mining container was removed after execution and
+the canonical Triton predecessor was verified healthy and unchanged.
+
+This closes evidence preparation, not semantic quality. The cases are
+diagnostic samples rather than independent route truth; native-versus-legacy
+count differences are not a verdict because the legacy `704×704` path stretches
+the raw 4:3 image. Accordingly `review_ready=true`, while ground truth,
+candidate acceptance, production acceptance, navigation, safety, commands and
+actuation authority remain false. The next action is operator adjudication in
+the existing M4.8 review instrument.
+
+### 2026-08-26 — M4.8R2 conservative static-occupancy qualification
+
+M4.8R2 moves the small-static problem out of semantic detector tuning and into
+the existing LiDAR occupancy boundary. RF-DETR, native fisheye input and its
+risk taxonomy are unchanged. The deterministic qualification consumes the
+accepted M4.7 current/rolling graph plus the frozen M4.8R1 operator-assisted
+static anchors. It evaluates one already sealed local-surface signal,
+`point_step_candidate`, only as additive occupied-or-unknown evidence. It never
+clears a cell, claims free space, starts detector inference or uses the GPU.
+
+Immutable result
+`m48-static-occupancy-qualification-568024554cff011332ff19ca4739f70555a6232c0607dec2a71be6db408ea69a`
+contains `11` static passage anchors. The accepted graph qualifies `6/11`; the
+additive low-step candidate qualifies `10/11`. In the critical `0–8 m` band the
+change is `6/9 → 9/9`; in the `8–12 m` approach band it is `0/2 → 1/2`. All
+four existing canonical engineering anchors remain matched and the result
+contains zero false-free claims. One approach anchor remains explicitly
+`unresolved-unknown-never-free`.
+
+This is candidate-visible development evidence, not independent truth or a
+production cutover. The result accepts only a bounded next action: integrate
+the low-step contribution as an occupied-only Worker shadow and replay all
+`4,489` frames on Worker 006 while measuring effective FPS, stage latency,
+occupancy/component growth, capacity drops and the same static anchors. The LAB
+reuses the M4.7 `VIDEO/CAMERA/3D/PLAN/SEMANTICS` viewer and projects the eleven
+anchors onto its immutable timeline; no third perception instrument exists.
+Navigation, commands, actuation, physical clearance and collision-safety
+authority remain false.
+
 ## Implementation order
 
 The implementation sequence is intentionally strict:

experiments/perception/run_m48q_native_risk_case_mining_worker.py

@@ -0,0 +1,677 @@
+#!/usr/bin/env python3
+"""Mine bounded native raw-fisheye risk cases from immutable Worker 006 ledgers."""
+
+from __future__ import annotations
+
+import argparse
+import hashlib
+import json
+import math
+import sys
+from collections import Counter
+from collections.abc import Iterable, Mapping, Sequence
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Any, Final
+
+PROFILE_SCHEMA: Final = "missioncore.m48q-native-risk-case-mining-profile/v1"
+RESULT_SCHEMA: Final = "missioncore.m48q-native-risk-case-mining-result/v1"
+CASE_SCHEMA: Final = "missioncore.m48q-native-risk-review-case/v1"
+GRAPH_FRAME_SCHEMA: Final = "missioncore.m48s-reference-graph-frame-evidence/v1"
+COMPARISON_FRAME_SCHEMA: Final = "missioncore.m48n-native-vs-704-frame/v0"
+FALSE_AUTHORITY: Final = {
+    "ground_truth": False,
+    "candidate_accepted": False,
+    "commands_enabled": False,
+    "actuation_allowed": False,
+    "navigation_or_safety_accepted": False,
+}
+
+
+class M48QCaseMiningError(RuntimeError):
+    """Raised when immutable native review evidence is inconsistent."""
+
+
+@dataclass(frozen=True, slots=True)
+class Proposal:
+    proposal_id: str
+    class_name: str
+    risk_family: str
+    score: float
+    box_xyxy: tuple[float, float, float, float]
+
+
+@dataclass(frozen=True, slots=True)
+class FrameCandidate:
+    sequence: int
+    frame_id: str
+    evidence_time_ns: int
+    proposals: tuple[Proposal, ...]
+    native_count: int
+    legacy_count: int
+    matched_count: int
+    buckets: frozenset[str]
+
+
+def canonical_json(value: object) -> bytes:
+    return json.dumps(
+        value,
+        ensure_ascii=False,
+        sort_keys=True,
+        separators=(",", ":"),
+        allow_nan=False,
+    ).encode("utf-8")
+
+
+def sha256_path(path: Path) -> str:
+    digest = hashlib.sha256()
+    with path.open("rb") as stream:
+        for chunk in iter(lambda: stream.read(1024 * 1024), b""):
+            digest.update(chunk)
+    return digest.hexdigest()
+
+
+def _read_object(path: Path) -> dict[str, Any]:
+    try:
+        value: object = json.loads(path.read_text("utf-8"))
+    except (OSError, json.JSONDecodeError) as exc:
+        raise M48QCaseMiningError(f"cannot read JSON object: {path.name}") from exc
+    if not isinstance(value, dict):
+        raise M48QCaseMiningError(f"JSON evidence is not an object: {path.name}")
+    return value
+
+
+def _verify_hash(path: Path, expected: str, label: str) -> str:
+    actual = sha256_path(path)
+    if actual != expected:
+        raise M48QCaseMiningError(f"{label} SHA-256 changed: {actual}")
+    return actual
+
+
+def _risk_family_map(profile: Mapping[str, Any]) -> dict[str, str]:
+    raw = profile.get("risk_families")
+    if not isinstance(raw, dict):
+        raise M48QCaseMiningError("risk family profile is invalid")
+    result: dict[str, str] = {}
+    for family, classes in raw.items():
+        if (
+            family not in {"person", "animal", "light-road-user", "vehicle"}
+            or not isinstance(classes, list)
+            or not classes
+        ):
+            raise M48QCaseMiningError("risk family profile changed")
+        for class_name in classes:
+            if not isinstance(class_name, str) or class_name in result:
+                raise M48QCaseMiningError("risk classes are invalid or duplicated")
+            result[class_name] = family
+    return result
+
+
+def _proposal(
+    value: object,
+    *,
+    sequence: int,
+    profile: Mapping[str, Any],
+    families: Mapping[str, str],
+) -> Proposal:
+    if not isinstance(value, dict):
+        raise M48QCaseMiningError("detector proposal is not an object")
+    candidate = profile["candidate"]
+    expected_frame_id = f"frame-{sequence:06d}"
+    if (
+        value.get("frame_id") != expected_frame_id
+        or value.get("provider_id") != candidate["provider_id"]
+        or value.get("model_id") != candidate["model_id"]
+        or value.get("preprocess_id") != candidate["preprocess_id"]
+    ):
+        raise M48QCaseMiningError("native detector proposal identity changed")
+    proposal_id = value.get("proposal_id")
+    class_name = value.get("semantic_hint")
+    score = value.get("objectness")
+    region = value.get("region")
+    if (
+        not isinstance(proposal_id, str)
+        or not isinstance(class_name, str)
+        or class_name not in families
+        or not isinstance(score, (float, int))
+        or isinstance(score, bool)
+        or not math.isfinite(float(score))
+        or float(score) < candidate["minimum_score"]
+        or not isinstance(region, dict)
+    ):
+        raise M48QCaseMiningError("native detector proposal contract changed")
+    coordinates = tuple(region.get(key) for key in ("x_min", "y_min", "x_max", "y_max"))
+    if not all(
+        isinstance(item, (float, int)) and not isinstance(item, bool) and math.isfinite(float(item))
+        for item in coordinates
+    ):
+        raise M48QCaseMiningError("native detector box is invalid")
+    left, top, right, bottom = (float(item) for item in coordinates)
+    source = profile["source"]
+    if not (
+        0 <= left < right <= source["raster_width"] and 0 <= top < bottom <= source["raster_height"]
+    ):
+        raise M48QCaseMiningError("native detector box escaped the raw source raster")
+    return Proposal(
+        proposal_id=proposal_id,
+        class_name=class_name,
+        risk_family=families[class_name],
+        score=float(score),
+        box_xyxy=(left, top, right, bottom),
+    )
+
+
+def load_comparison_rows(path: Path, expected_count: int) -> dict[int, tuple[int, int, int]]:
+    rows: dict[int, tuple[int, int, int]] = {}
+    try:
+        with path.open("r", encoding="utf-8") as stream:
+            for line_number, line in enumerate(stream, start=1):
+                value = json.loads(line)
+                if not isinstance(value, dict):
+                    raise M48QCaseMiningError("comparison frame is not an object")
+                if value.get("schema_version") not in {None, COMPARISON_FRAME_SCHEMA}:
+                    raise M48QCaseMiningError("comparison frame schema changed")
+                sequence = value.get("frame_index")
+                counts = tuple(
+                    value.get(key)
+                    for key in (
+                        "native_detection_count",
+                        "baseline_detection_count",
+                        "matched_detection_count_iou_at_least_0_5",
+                    )
+                )
+                if (
+                    not isinstance(sequence, int)
+                    or isinstance(sequence, bool)
+                    or sequence in rows
+                    or not all(
+                        isinstance(item, int) and not isinstance(item, bool) and item >= 0
+                        for item in counts
+                    )
+                ):
+                    raise M48QCaseMiningError(f"comparison frame {line_number} is invalid")
+                rows[sequence] = counts
+    except (OSError, json.JSONDecodeError) as exc:
+        raise M48QCaseMiningError("comparison frame ledger cannot be read") from exc
+    if set(rows) != set(range(expected_count)):
+        raise M48QCaseMiningError("comparison frame ledger is incomplete")
+    return rows
+
+
+def _case_buckets(
+    proposals: Sequence[Proposal],
+    *,
+    native_count: int,
+    legacy_count: int,
+    profile: Mapping[str, Any],
+) -> frozenset[str]:
+    selection = profile["selection"]
+    buckets = {item.risk_family for item in proposals}
+    if any(item.score <= selection["low_confidence_maximum_score"] for item in proposals):
+        buckets.add("low-confidence")
+    width = profile["source"]["raster_width"]
+    height = profile["source"]["raster_height"]
+    margin = selection["fisheye_edge_margin_fraction"]
+    if any(
+        item.box_xyxy[0] <= width * margin
+        or item.box_xyxy[2] >= width * (1 - margin)
+        or item.box_xyxy[1] <= height * margin
+        or item.box_xyxy[3] >= height * (1 - margin)
+        for item in proposals
+    ):
+        buckets.add("fisheye-edge")
+    if native_count < legacy_count:
+        buckets.add("native-fewer-than-legacy")
+    elif native_count > legacy_count:
+        buckets.add("native-more-than-legacy")
+    return frozenset(buckets)
+
+
+def load_graph_candidates(
+    path: Path,
+    *,
+    profile: Mapping[str, Any],
+    comparisons: Mapping[int, tuple[int, int, int]],
+) -> list[FrameCandidate]:
+    families = _risk_family_map(profile)
+    expected_count = profile["source"]["frame_count"]
+    candidates: list[FrameCandidate] = []
+    try:
+        with path.open("r", encoding="utf-8") as stream:
+            for sequence, line in enumerate(stream):
+                value = json.loads(line)
+                if not isinstance(value, dict) or value.get("schema_version") != GRAPH_FRAME_SCHEMA:
+                    raise M48QCaseMiningError("graph frame schema changed")
+                source = value.get("source_envelope")
+                raw_proposals = value.get("detector_proposals")
+                if (
+                    not isinstance(source, dict)
+                    or source.get("sequence") != sequence
+                    or source.get("frame_id") != f"frame-{sequence:06d}"
+                    or not isinstance(raw_proposals, list)
+                    or value.get("authority") != FALSE_AUTHORITY
+                ):
+                    raise M48QCaseMiningError("graph frame identity or authority changed")
+                timestamps = source.get("timestamps")
+                evidence_time_ns = (
+                    timestamps.get("source_ns") if isinstance(timestamps, dict) else None
+                )
+                if (
+                    not isinstance(evidence_time_ns, int)
+                    or isinstance(evidence_time_ns, bool)
+                    or evidence_time_ns < 0
+                ):
+                    raise M48QCaseMiningError("graph frame evidence time is invalid")
+                proposals = tuple(
+                    _proposal(item, sequence=sequence, profile=profile, families=families)
+                    for item in raw_proposals
+                )
+                native_count, legacy_count, matched_count = comparisons[sequence]
+                if len(proposals) != native_count:
+                    raise M48QCaseMiningError("native graph/comparison detector count changed")
+                buckets = _case_buckets(
+                    proposals,
+                    native_count=native_count,
+                    legacy_count=legacy_count,
+                    profile=profile,
+                )
+                candidates.append(
+                    FrameCandidate(
+                        sequence=sequence,
+                        frame_id=source["frame_id"],
+                        evidence_time_ns=evidence_time_ns,
+                        proposals=proposals,
+                        native_count=native_count,
+                        legacy_count=legacy_count,
+                        matched_count=matched_count,
+                        buckets=buckets,
+                    )
+                )
+    except (OSError, json.JSONDecodeError) as exc:
+        raise M48QCaseMiningError("graph frame ledger cannot be read") from exc
+    if len(candidates) != expected_count:
+        raise M48QCaseMiningError("graph frame ledger is incomplete")
+    return candidates
+
+
+def _quantile_order(items: Sequence[FrameCandidate]) -> Iterable[FrameCandidate]:
+    if not items:
+        return ()
+    indexes: list[int] = []
+    left = 0
+    right = len(items) - 1
+    while left <= right:
+        middle = (left + right) // 2
+        indexes.append(middle)
+        if middle - left > 0:
+            indexes.append((left + middle - 1) // 2)
+        if right - middle > 0:
+            indexes.append((middle + 1 + right) // 2)
+        left += 1
+        right -= 1
+    seen: set[int] = set()
+    return (items[index] for index in indexes if not (index in seen or seen.add(index)))
+
+
+def select_cases(
+    candidates: Sequence[FrameCandidate],
+    *,
+    bucket_quotas: Mapping[str, int],
+    minimum_sequence_separation: int,
+) -> list[FrameCandidate]:
+    selected: list[FrameCandidate] = []
+    selected_sequences: set[int] = set()
+    for bucket, quota in bucket_quotas.items():
+        eligible = [item for item in candidates if bucket in item.buckets]
+        admitted = 0
+        for item in _quantile_order(eligible):
+            if item.sequence in selected_sequences:
+                continue
+            if any(
+                abs(item.sequence - prior.sequence) < minimum_sequence_separation
+                for prior in selected
+            ):
+                continue
+            selected.append(item)
+            selected_sequences.add(item.sequence)
+            admitted += 1
+            if admitted == quota:
+                break
+        if admitted != quota:
+            raise M48QCaseMiningError(
+                f"selection bucket {bucket} produced {admitted}/{quota} separated cases"
+            )
+    expected = sum(bucket_quotas.values())
+    if len(selected) != expected:
+        raise M48QCaseMiningError("selected case count changed")
+    return sorted(selected, key=lambda item: item.sequence)
+
+
+def render_selected_frames(
+    *,
+    video_path: Path,
+    selected: Sequence[FrameCandidate],
+    cases_root: Path,
+    width: int,
+    height: int,
+) -> dict[int, dict[str, object]]:
+    import av
+    from av.error import FFmpegError
+    from PIL import Image
+
+    wanted = {item.sequence for item in selected}
+    rendered: dict[int, dict[str, object]] = {}
+    cases_root.mkdir(mode=0o700, parents=True, exist_ok=False)
+    try:
+        with av.open(str(video_path), mode="r") as container:
+            streams = list(container.streams.video)
+            if len(streams) != 1:
+                raise M48QCaseMiningError("RAVNOVES00 video stream contract changed")
+            for sequence, frame in enumerate(container.decode(streams[0])):
+                if sequence not in wanted:
+                    continue
+                array = frame.to_ndarray(format="rgb24")
+                if array.shape != (height, width, 3):
+                    raise M48QCaseMiningError("decoded raw-fisheye raster changed")
+                name = f"frame-{sequence:06d}.jpg"
+                path = cases_root / name
+                Image.fromarray(array, mode="RGB").save(
+                    path,
+                    format="JPEG",
+                    quality=94,
+                    subsampling=0,
+                    optimize=False,
+                )
+                rendered[sequence] = {
+                    "path": f"cases/{name}",
+                    "media_type": "image/jpeg",
+                    "width": width,
+                    "height": height,
+                    "byte_length": path.stat().st_size,
+                    "sha256": sha256_path(path),
+                    "geometric_resampling": False,
+                }
+                if len(rendered) == len(wanted):
+                    break
+    except (FFmpegError, OSError) as exc:
+        raise M48QCaseMiningError("RAVNOVES00 raw-fisheye frames cannot be decoded") from exc
+    if set(rendered) != wanted:
+        raise M48QCaseMiningError("not every selected raw-fisheye frame was decoded")
+    return rendered
+
+
+def _case_document(
+    candidate: FrameCandidate,
+    *,
+    image: Mapping[str, object],
+) -> dict[str, object]:
+    return {
+        "schema_version": CASE_SCHEMA,
+        "case_id": f"{candidate.sequence:06d}",
+        "sequence": candidate.sequence,
+        "frame_id": candidate.frame_id,
+        "evidence_time_ns": candidate.evidence_time_ns,
+        "selection_buckets": sorted(candidate.buckets),
+        "comparison": {
+            "native_detection_count": candidate.native_count,
+            "legacy_704_detection_count": candidate.legacy_count,
+            "matched_detection_count_iou_at_least_0_5": candidate.matched_count,
+            "quality_interpretation": "diagnostic-only",
+        },
+        "image": dict(image),
+        "proposals": [
+            {
+                "proposal_id": item.proposal_id,
+                "class_name": item.class_name,
+                "risk_family": item.risk_family,
+                "score": round(item.score, 9),
+                "box_xyxy": [round(value, 6) for value in item.box_xyxy],
+            }
+            for item in candidate.proposals
+        ],
+        "ground_truth": False,
+        "quality_evaluated": False,
+        "authority": dict(FALSE_AUTHORITY),
+    }
+
+
+def run(args: argparse.Namespace) -> dict[str, object]:
+    for path in (
+        args.profile,
+        args.graph_result,
+        args.graph_frames,
+        args.comparison_result,
+        args.comparison_frames,
+        args.video,
+    ):
+        if path.is_symlink() or not path.is_file():
+            raise M48QCaseMiningError(f"required evidence is missing: {path.name}")
+    profile_sha256 = _verify_hash(args.profile, args.expected_profile_sha256, "profile")
+    graph_result_sha256 = _verify_hash(
+        args.graph_result, args.expected_graph_result_sha256, "graph result"
+    )
+    graph_frames_sha256 = _verify_hash(
+        args.graph_frames, args.expected_graph_frames_sha256, "graph frames"
+    )
+    comparison_result_sha256 = _verify_hash(
+        args.comparison_result,
+        args.expected_comparison_result_sha256,
+        "comparison result",
+    )
+    comparison_frames_sha256 = _verify_hash(
+        args.comparison_frames,
+        args.expected_comparison_frames_sha256,
+        "comparison frames",
+    )
+    video_sha256 = _verify_hash(args.video, args.expected_video_sha256, "video")
+    runner_sha256 = _verify_hash(Path(__file__), args.expected_runner_sha256, "runner")
+
+    profile = _read_object(args.profile)
+    graph_result = _read_object(args.graph_result)
+    comparison_result = _read_object(args.comparison_result)
+    source = profile.get("source")
+    candidate = profile.get("candidate")
+    selection = profile.get("selection")
+    scope = profile.get("scope")
+    if (
+        profile.get("schema_version") != PROFILE_SCHEMA
+        or not isinstance(source, dict)
+        or source.get("video_sha256") != video_sha256
+        or source.get("raster_width") != 800
+        or source.get("raster_height") != 600
+        or source.get("frame_count") != 4489
+        or source.get("geometric_resampling") is not False
+        or source.get("rectification") is not False
+        or source.get("warp") is not False
+        or not isinstance(candidate, dict)
+        or candidate.get("engine_sha256")
+        != "b8a40b3580edff001ec9680de68707242294ff590ab296000fae371f1083f695"
+        or not isinstance(selection, dict)
+        or selection.get("case_count") != 24
+        or not isinstance(selection.get("bucket_quotas"), dict)
+        or sum(selection["bucket_quotas"].values()) != 24
+        or scope
+        != {
+            "quality_evaluated": False,
+            "ground_truth": False,
+            "candidate_accepted": False,
+            "production_accepted": False,
+            "purpose": "bounded-native-risk-case-review",
+        }
+        or profile.get("authority") != FALSE_AUTHORITY
+    ):
+        raise M48QCaseMiningError("M4.8Q profile contract changed")
+    if (
+        graph_result.get("schema_version") != "missioncore.m48s-reference-graph-shadow-load/v5"
+        or graph_result.get("completed") is not True
+        or graph_result.get("identity", {}).get("detector_provider_id") != candidate["provider_id"]
+        or graph_result.get("identity", {}).get("inputs", {}).get("video") != video_sha256
+        or graph_result.get("execution", {}).get("frame_evidence", {}).get("sha256")
+        != graph_frames_sha256
+        or graph_result.get("authority") != FALSE_AUTHORITY
+        or graph_result.get("production_accepted") is not False
+    ):
+        raise M48QCaseMiningError("native graph result contract changed")
+    if (
+        comparison_result.get("schema_version") != "missioncore.m48n-native-vs-704-ravnoves00/v0"
+        or comparison_result.get("completed") is not True
+        or comparison_result.get("source", {}).get("video_sha256") != video_sha256
+        or comparison_result.get("source", {}).get("frame_count") != source["frame_count"]
+        or comparison_result.get("execution", {}).get("frames_sha256") != comparison_frames_sha256
+        or comparison_result.get("authority") != FALSE_AUTHORITY
+    ):
+        raise M48QCaseMiningError("native/legacy comparison result contract changed")
+
+    output_root = args.output_root
+    if output_root.exists():
+        raise M48QCaseMiningError("M4.8Q output root already exists")
+    output_root.mkdir(mode=0o700, parents=True)
+    comparisons = load_comparison_rows(args.comparison_frames, source["frame_count"])
+    candidates = load_graph_candidates(
+        args.graph_frames,
+        profile=profile,
+        comparisons=comparisons,
+    )
+    selected = select_cases(
+        candidates,
+        bucket_quotas=selection["bucket_quotas"],
+        minimum_sequence_separation=selection["minimum_sequence_separation"],
+    )
+    rendered = render_selected_frames(
+        video_path=args.video,
+        selected=selected,
+        cases_root=output_root / "cases",
+        width=source["raster_width"],
+        height=source["raster_height"],
+    )
+    cases = [
+        _case_document(
+            item,
+            image=rendered[item.sequence],
+        )
+        for item in selected
+    ]
+    cases_path = output_root / "cases.jsonl"
+    with cases_path.open("xb") as stream:
+        for case in cases:
+            stream.write(canonical_json(case) + b"\n")
+
+    class_counts = Counter(proposal.class_name for item in selected for proposal in item.proposals)
+    selected_bucket_coverage = Counter(bucket for item in selected for bucket in item.buckets)
+    identity = {
+        "schema_version": RESULT_SCHEMA,
+        "profile": {"profile_id": profile["profile_id"], "sha256": profile_sha256},
+        "source": {
+            "source_id": source["source_id"],
+            "video_sha256": video_sha256,
+            "graph_result_sha256": graph_result_sha256,
+            "graph_frames_sha256": graph_frames_sha256,
+            "comparison_result_sha256": comparison_result_sha256,
+            "comparison_frames_sha256": comparison_frames_sha256,
+        },
+        "candidate": dict(candidate),
+        "runner_sha256": runner_sha256,
+        "cases_sha256": sha256_path(cases_path),
+        "authority": dict(FALSE_AUTHORITY),
+    }
+    result: dict[str, object] = {
+        "schema_version": RESULT_SCHEMA,
+        "status": "complete-review-ready-quality-not-adjudicated",
+        "completed": True,
+        "worker": {"worker_id": "worker-006", "node": "DESKTOP-OPJ8J04"},
+        "identity": identity,
+        "report_identity_sha256": hashlib.sha256(canonical_json(identity)).hexdigest(),
+        "source": {
+            **dict(source),
+            "graph_result_sha256": graph_result_sha256,
+            "graph_frames_sha256": graph_frames_sha256,
+            "comparison_result_sha256": comparison_result_sha256,
+            "comparison_frames_sha256": comparison_frames_sha256,
+        },
+        "candidate": dict(candidate),
+        "selection": {
+            "case_count": len(cases),
+            "minimum_sequence_separation": selection["minimum_sequence_separation"],
+            "configured_bucket_quotas": selection["bucket_quotas"],
+            "selected_bucket_coverage": dict(sorted(selected_bucket_coverage.items())),
+            "selected_sequences": [item.sequence for item in selected],
+            "selected_class_counts": dict(sorted(class_counts.items())),
+        },
+        "artifacts": {
+            "cases": {
+                "path": "cases.jsonl",
+                "schema_version": CASE_SCHEMA,
+                "row_count": len(cases),
+                "sha256": sha256_path(cases_path),
+            },
+            "images": {
+                "root": "cases",
+                "count": len(rendered),
+                "geometric_resampling": False,
+            },
+        },
+        "decision": {
+            "quality_evaluated": False,
+            "ground_truth": False,
+            "candidate_accepted": False,
+            "production_accepted": False,
+            "next_action": "operator-adjudication-in-existing-m48-review-instrument",
+        },
+        "limitations": [
+            "The selected RAVNOVES00 cases are diagnostic samples, not independent truth.",
+            (
+                "Native-versus-legacy detection-count differences are not quality "
+                "verdicts because legacy 704 stretches the raw 4:3 raster."
+            ),
+            (
+                "No child/adult, behavior, physical track identity, navigation or "
+                "actuation claim is made."
+            ),
+            (
+                "JPEG review derivatives preserve the 800x600 raster without geometric "
+                "resampling but are not lossless source frames."
+            ),
+        ],
+        "authority": dict(FALSE_AUTHORITY),
+    }
+    (output_root / "result.json").write_bytes(canonical_json(result) + b"\n")
+    return result
+
+
+def parse_args(argv: Sequence[str] | None = None) -> argparse.Namespace:
+    parser = argparse.ArgumentParser(description=__doc__)
+    for name in (
+        "profile",
+        "graph-result",
+        "graph-frames",
+        "comparison-result",
+        "comparison-frames",
+        "video",
+        "output-root",
+    ):
+        parser.add_argument(f"--{name}", type=Path, required=True)
+    for name in (
+        "profile",
+        "graph-result",
+        "graph-frames",
+        "comparison-result",
+        "comparison-frames",
+        "video",
+        "runner",
+    ):
+        parser.add_argument(f"--expected-{name}-sha256", required=True)
+    return parser.parse_args(argv)
+
+
+def main(argv: Sequence[str] | None = None) -> int:
+    try:
+        result = run(parse_args(argv))
+    except M48QCaseMiningError as exc:
+        print(f"M4.8Q case mining refused: {exc}", file=sys.stderr)
+        return 2
+    print(json.dumps(result, ensure_ascii=False, sort_keys=True))
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

experiments/perception/seal_m48q_native_risk_quality_lab.py

@@ -0,0 +1,39 @@
+#!/usr/bin/env python3
+"""Publish the immutable M4.8Q native raw-fisheye review LAB result."""
+
+from __future__ import annotations
+
+import argparse
+import json
+from pathlib import Path
+
+from k1link.laboratory.m48q_native_risk_quality_lab import (
+    build_m48q_native_risk_quality_lab,
+)
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--repository-root", type=Path, required=True)
+    parser.add_argument("--output-root", type=Path, required=True)
+    arguments = parser.parse_args()
+    result = build_m48q_native_risk_quality_lab(
+        repository_root=arguments.repository_root,
+        output_root=arguments.output_root,
+    )
+    print(
+        json.dumps(
+            {
+                "result_id": result.result_id,
+                "result_root": str(result.result_root),
+                "status": result.manifest["status"],
+            },
+            ensure_ascii=False,
+            sort_keys=True,
+        )
+    )
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

experiments/perception/worker/Invoke-M48QNativeRiskCaseMining.ps1

@@ -0,0 +1,207 @@
+[CmdletBinding()]
+param(
+    [Parameter(Mandatory = $true)]
+    [string]$ReleaseRoot,
+    [Parameter(Mandatory = $true)]
+    [ValidatePattern("^[A-Za-z0-9._-]{1,96}$")]
+    [string]$RunId,
+    [string]$OutputRoot = "D:\NDC_MISSIONCORE\runtime\results\m48q-native-risk-case-mining"
+)
+
+$ErrorActionPreference = "Stop"
+$ProgressPreference = "SilentlyContinue"
+
+function Assert-LastExitCode([string]$Operation) {
+    if ($LASTEXITCODE -ne 0) { throw "$Operation failed with exit code $LASTEXITCODE" }
+}
+
+function Get-Sha256([string]$Path) {
+    return (Get-FileHash -LiteralPath $Path -Algorithm SHA256).Hash.ToLowerInvariant()
+}
+
+function Resolve-DDirectory([string]$Path, [string]$Label, [bool]$Create) {
+    if ($Create -and -not (Test-Path -LiteralPath $Path)) {
+        $null = New-Item -ItemType Directory -Path $Path
+    }
+    $item = Get-Item -LiteralPath (Resolve-Path -LiteralPath $Path).Path -Force
+    if (
+        -not $item.PSIsContainer -or
+        ($item.Attributes -band [IO.FileAttributes]::ReparsePoint) -or
+        [IO.Path]::GetPathRoot($item.FullName).TrimEnd("\") -ine "D:"
+    ) {
+        throw "$Label must be a real D: directory"
+    }
+    return $item.FullName
+}
+
+function Assert-RegularFile([string]$Path, [string]$Label) {
+    $item = Get-Item -LiteralPath (Resolve-Path -LiteralPath $Path).Path -Force
+    if ($item.PSIsContainer -or ($item.Attributes -band [IO.FileAttributes]::ReparsePoint)) {
+        throw "$Label must be a regular file"
+    }
+    return $item.FullName
+}
+
+function Convert-ToDockerPath([string]$Path) { return $Path.Replace("\", "/") }
+
+function Get-Container([string]$Name) {
+    $rows = @((& docker inspect $Name) | ConvertFrom-Json)
+    Assert-LastExitCode "Docker inspection for $Name"
+    if ($rows.Count -ne 1) { throw "Container identity for $Name is not unique" }
+    return $rows[0]
+}
+
+if ($env:COMPUTERNAME -cne "DESKTOP-OPJ8J04") {
+    throw "M4.8Q native risk case mining is pinned to DESKTOP-OPJ8J04"
+}
+
+$release = Resolve-DDirectory $ReleaseRoot "M4.8Q release root" $false
+$output = Resolve-DDirectory $OutputRoot "M4.8Q output root" $true
+$runOutput = Join-Path $output $RunId
+if (Test-Path -LiteralPath $runOutput) { throw "M4.8Q output already exists" }
+
+$runner = Assert-RegularFile (
+    Join-Path $release "run_m48q_native_risk_case_mining_worker.py"
+) "M4.8Q runner"
+$profile = Assert-RegularFile (
+    Join-Path $release "m48q-native-risk-case-mining-v1.json"
+) "M4.8Q profile"
+$runnerSha256 = Get-Sha256 $runner
+$profileSha256 = Get-Sha256 $profile
+if ($runnerSha256 -cne "39bb1d810b167d6e97dcb091505b52d4a812d69419dcb32fe23ea5d14d605d67") {
+    throw "M4.8Q runner SHA-256 changed"
+}
+if ($profileSha256 -cne "c455055e63578d505edc80b66d67e795916a3d0297cc18bfee5a6af7b032ceda") {
+    throw "M4.8Q profile SHA-256 changed"
+}
+
+$graphRoot = Resolve-DDirectory (
+    "D:\NDC_MISSIONCORE\runtime\results\m48n-native-reference-graph-shadow\ravnoves00-full-12fps-v0"
+) "M4.8Q graph evidence root" $false
+$comparisonRoot = Resolve-DDirectory (
+    "D:\NDC_MISSIONCORE\runtime\results\m48n-native-vs-704\ravnoves00-full-v0"
+) "M4.8Q comparison evidence root" $false
+$graphResult = Assert-RegularFile (Join-Path $graphRoot "result.json") "graph result"
+$graphFrames = Assert-RegularFile (Join-Path $graphRoot "frames.jsonl") "graph frames"
+$comparisonResult = Assert-RegularFile (Join-Path $comparisonRoot "result.json") "comparison result"
+$comparisonFrames = Assert-RegularFile (Join-Path $comparisonRoot "frames.jsonl") "comparison frames"
+$video = Assert-RegularFile (
+    "D:\NDC_MISSIONCORE\runtime\experiments\e46e\inputs\right-cadd1696ff000904eb78633a0a8418104b8024f178b91f3421789021ccb160e8.mp4"
+) "RAVNOVES00 video"
+
+$graphResultSha256 = Get-Sha256 $graphResult
+$graphFramesSha256 = Get-Sha256 $graphFrames
+$comparisonResultSha256 = Get-Sha256 $comparisonResult
+$comparisonFramesSha256 = Get-Sha256 $comparisonFrames
+$videoSha256 = Get-Sha256 $video
+if ($graphResultSha256 -cne "c5c3a831b1d1c3271161c91fa5c5c40533eb663ca288ed0220334a147aed6e15") {
+    throw "M4.8Q graph result SHA-256 changed"
+}
+if ($graphFramesSha256 -cne "b245af969600670d0975e89cae02b44206e3f1328eff48d5b4639b1b2ab57346") {
+    throw "M4.8Q graph frame evidence SHA-256 changed"
+}
+if ($comparisonResultSha256 -cne "fd91c2f1f477038d5af51656d510aba39d69ad2e1a387f15d98ade19dd3a0c49") {
+    throw "M4.8Q comparison result SHA-256 changed"
+}
+if ($comparisonFramesSha256 -cne "6a35125d4e003edfd8a33b4239bad0910f137fde3a770e9d5baab721cdc145b2") {
+    throw "M4.8Q comparison frame evidence SHA-256 changed"
+}
+if ($videoSha256 -cne "cadd1696ff000904eb78633a0a8418104b8024f178b91f3421789021ccb160e8") {
+    throw "RAVNOVES00 video SHA-256 changed"
+}
+
+$media = Resolve-DDirectory (
+    "D:\NDC_MISSIONCORE\runtime\derived\perception-e15-media-pyav180-lz445-v1"
+) "PyAV dependency" $false
+$pillow = Resolve-DDirectory (
+    "D:\NDC_MISSIONCORE\runtime\derived\perception-p0-env-v1"
+) "Pillow dependency" $false
+$image = (
+    "nvcr.io/nvidia/tritonserver:26.06-py3@" +
+    "sha256:58df7489c3f2276f9591d500a012dee03e23d35543ce3c390b4c001e6bf90794"
+)
+& docker image inspect $image *> $null
+Assert-LastExitCode "pinned M4.8Q image inspection"
+
+$canonicalTriton = Get-Container "ndc-mission-core-triton"
+if (-not $canonicalTriton.State.Running -or $canonicalTriton.State.Health.Status -cne "healthy") {
+    throw "Canonical Triton must remain healthy during M4.8Q mining"
+}
+$canonicalTritonId = [string]$canonicalTriton.Id
+$runnerName = "ndc-mission-core-m48q-native-risk-case-mining"
+if (& docker ps -a --format "{{.Names}}" --filter "name=^/$runnerName$") {
+    throw "M4.8Q bounded container already exists"
+}
+
+try {
+    & docker run `
+        --name $runnerName `
+        --label "com.nodedc.product=mission-core" `
+        --label "com.nodedc.stack=ndc-mission-core-compute" `
+        --label "com.nodedc.role=bounded-native-risk-case-mining" `
+        --label "com.nodedc.managed-by=codex-bounded-experiment" `
+        --network none `
+        --read-only `
+        --security-opt "no-new-privileges:true" `
+        --cap-drop ALL `
+        --pids-limit 128 `
+        --cpus 4 `
+        --memory 4g `
+        --tmpfs "/tmp:rw,noexec,nosuid,size=512m" `
+        -e "PYTHONDONTWRITEBYTECODE=1" `
+        -e "PYTHONPATH=/opt/media:/opt/pillow" `
+        -v ((Convert-ToDockerPath $release) + ":/release:ro") `
+        -v ((Convert-ToDockerPath $output) + ":/output:rw") `
+        -v ((Convert-ToDockerPath $media) + ":/opt/media:ro") `
+        -v ((Convert-ToDockerPath $pillow) + ":/opt/pillow:ro") `
+        -v ((Convert-ToDockerPath $graphRoot) + ":/evidence/graph:ro") `
+        -v ((Convert-ToDockerPath $comparisonRoot) + ":/evidence/comparison:ro") `
+        -v ((Convert-ToDockerPath $video) + ":/source/right.mp4:ro") `
+        --entrypoint python3 `
+        $image `
+        /release/run_m48q_native_risk_case_mining_worker.py `
+        --profile /release/m48q-native-risk-case-mining-v1.json `
+        --graph-result /evidence/graph/result.json `
+        --graph-frames /evidence/graph/frames.jsonl `
+        --comparison-result /evidence/comparison/result.json `
+        --comparison-frames /evidence/comparison/frames.jsonl `
+        --video /source/right.mp4 `
+        --output-root ("/output/{0}" -f $RunId) `
+        --expected-profile-sha256 $profileSha256 `
+        --expected-graph-result-sha256 $graphResultSha256 `
+        --expected-graph-frames-sha256 $graphFramesSha256 `
+        --expected-comparison-result-sha256 $comparisonResultSha256 `
+        --expected-comparison-frames-sha256 $comparisonFramesSha256 `
+        --expected-video-sha256 $videoSha256 `
+        --expected-runner-sha256 $runnerSha256
+    Assert-LastExitCode "M4.8Q native risk case mining"
+    if (
+        -not (Test-Path -LiteralPath (Join-Path $runOutput "result.json") -PathType Leaf) -or
+        -not (Test-Path -LiteralPath (Join-Path $runOutput "cases.jsonl") -PathType Leaf) -or
+        @(Get-ChildItem -LiteralPath (Join-Path $runOutput "cases") -Filter "*.jpg" -File).Count -ne 24
+    ) {
+        throw "M4.8Q result artifacts are incomplete"
+    }
+} finally {
+    if (& docker ps -a --format "{{.Names}}" --filter "name=^/$runnerName$") {
+        & docker rm -f $runnerName *> $null
+    }
+    $canonicalAfter = Get-Container "ndc-mission-core-triton"
+    if (
+        [string]$canonicalAfter.Id -cne $canonicalTritonId -or
+        -not $canonicalAfter.State.Running -or
+        $canonicalAfter.State.Health.Status -cne "healthy"
+    ) {
+        throw "Canonical Triton changed during M4.8Q mining"
+    }
+}
+
+$result = Get-Content -LiteralPath (Join-Path $runOutput "result.json") -Raw | ConvertFrom-Json
+[pscustomobject]@{
+    run_id = $RunId
+    output_root = $runOutput
+    status = $result.status
+    case_count = $result.selection.case_count
+    report_identity_sha256 = $result.report_identity_sha256
+    canonical_triton = "healthy-and-unchanged"
+} | ConvertTo-Json -Depth 4

scripts/run_m48_static_occupancy_qualification.py

@@ -0,0 +1,81 @@
+#!/usr/bin/env python3
+"""Publish one canonical append-only M4.8R2 static-occupancy qualification."""
+
+from __future__ import annotations
+
+import argparse
+import json
+import socket
+from pathlib import Path
+
+from k1link.compute.pipeline_telemetry import JsonlPipelineTelemetrySink
+from k1link.laboratory import (
+    LaboratoryEvidenceRegistry,
+    LaboratoryExecutionRegistry,
+    LaboratoryRunner,
+    LaboratoryRunRequest,
+)
+
+
+def _parser() -> argparse.ArgumentParser:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--profile", type=Path, required=True)
+    parser.add_argument("--m47-lab-root", type=Path, required=True)
+    parser.add_argument("--graph-result-root", type=Path, required=True)
+    parser.add_argument("--small-static-result-root", type=Path, required=True)
+    parser.add_argument("--output-root", type=Path, required=True)
+    parser.add_argument("--receipt-root", type=Path, required=True)
+    parser.add_argument("--telemetry-path", type=Path, required=True)
+    parser.add_argument("--run-id", required=True)
+    parser.add_argument("--request-id", required=True)
+    return parser
+
+
+def main() -> int:
+    args = _parser().parse_args()
+    repository_root = Path(__file__).resolve().parents[1]
+    evidence = LaboratoryEvidenceRegistry.from_directory(
+        repository_root / "config" / "laboratories"
+    )
+    execution = LaboratoryExecutionRegistry.from_file(
+        repository_root / "config" / "laboratory-execution.json",
+        evidence,
+    )
+    runner = LaboratoryRunner(
+        registry=execution,
+        evidence_registry=evidence,
+        sink=JsonlPipelineTelemetrySink(args.telemetry_path),
+    )
+    result = runner.run(
+        LaboratoryRunRequest(
+            work_id="m48-static-occupancy-qualification",
+            run_id=args.run_id,
+            request_id=args.request_id,
+            contour_id="mission-core-laboratory",
+            agent_id="local-control-plane",
+            node_id=socket.gethostname(),
+            source_id="RAVNOVES00",
+            source_package_id=args.m47_lab_root.name,
+            method_id="m48-conservative-static-occupancy/v1",
+            inputs={
+                "repository_root": repository_root,
+                "profile_path": args.profile,
+                "m47_lab_root": args.m47_lab_root,
+                "graph_result_root": args.graph_result_root,
+                "small_static_result_root": args.small_static_result_root,
+            },
+            output_root=args.output_root,
+            receipt_root=args.receipt_root,
+        )
+    )
+    print(json.dumps({
+        "result_id": result.result_id,
+        "result_root": str(result.result_root),
+        "receipt_id": result.receipt_id,
+        "receipt_root": str(result.receipt_root),
+    }, ensure_ascii=False, sort_keys=True))
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

src/k1link/laboratory/execution.py

@@ -312,6 +312,9 @@ class LaboratoryRunner:
 
 def canonical_laboratory_adapters() -> dict[str, LaboratoryAdapter]:
     return {
+        "canonical.m48-static-occupancy-qualification/v1": (
+            _run_m48_static_occupancy_qualification
+        ),
         "canonical.m48-small-static-passage-regression/v1": (
             _run_m48_small_static_passage_regression
         ),
@@ -326,6 +329,27 @@ def canonical_laboratory_adapters() -> dict[str, LaboratoryAdapter]:
     }
 
 
+def _run_m48_static_occupancy_qualification(
+    request: LaboratoryRunRequest,
+) -> LaboratoryAdapterResult:
+    from k1link.laboratory.m48_static_occupancy_qualification import (
+        build_m48_static_occupancy_qualification,
+    )
+
+    result = build_m48_static_occupancy_qualification(
+        repository_root=request.inputs["repository_root"],
+        profile_path=request.inputs["profile_path"],
+        m47_lab_root=request.inputs["m47_lab_root"],
+        graph_result_root=request.inputs["graph_result_root"],
+        small_static_result_root=request.inputs["small_static_result_root"],
+        output_root=request.output_root,
+    )
+    return LaboratoryAdapterResult(
+        result_root=result.result_root,
+        result_id=result.result_id,
+    )
+
+
 def _run_m48s_fixed_class_detector(
     request: LaboratoryRunRequest,
 ) -> LaboratoryAdapterResult:

src/k1link/laboratory/m48_static_occupancy_qualification.py

@@ -0,0 +1,754 @@
+"""Immutable M4.8R2 qualification of conservative static LiDAR occupancy.
+
+The experiment does not run a detector and does not mutate the accepted M4.7
+graph.  It measures the accepted current/rolling occupied output on the frozen
+operator-assisted small-static anchors, then evaluates one additive CPU-only
+candidate already present in the local-surface artifact: low step candidates.
+Neither missing evidence nor a camera miss is ever converted to free space.
+"""
+
+from __future__ import annotations
+
+import hashlib
+import json
+import os
+import shutil
+import uuid
+from dataclasses import dataclass, replace
+from datetime import UTC, datetime
+from pathlib import Path
+from typing import Any, Final
+
+import numpy as np
+
+from k1link.laboratory.m47_reference_graph import (
+    M47ReferenceGraphLabError,
+    read_m47_reference_graph_lab,
+)
+from k1link.laboratory.m48_small_static_regression import (
+    M48SmallStaticRegressionError,
+    read_m48_small_static_passage_regression,
+)
+from k1link.perception.geometry import RecordedGeometryStore
+from k1link.perception.geometry_math import (
+    POINT_OCCUPIED,
+    project_map_points_kb4,
+    semantic_geometry_support,
+)
+
+M48_STATIC_OCCUPANCY_PROFILE_SCHEMA: Final = (
+    "missioncore.m48-static-occupancy-qualification-profile/v1"
+)
+M48_STATIC_OCCUPANCY_RESULT_SCHEMA: Final = (
+    "missioncore.m48-static-occupancy-qualification-result/v1"
+)
+M48_STATIC_OCCUPANCY_REPORT_SCHEMA: Final = (
+    "missioncore.m48-static-occupancy-qualification-report/v1"
+)
+M48_STATIC_OCCUPANCY_CASE_SCHEMA: Final = "missioncore.m48-static-occupancy-case/v1"
+M48_STATIC_OCCUPANCY_CANONICAL_SCHEMA: Final = (
+    "missioncore.m48-static-occupancy-canonical-anchor/v1"
+)
+M48_STATIC_OCCUPANCY_PREFIX: Final = "m48-static-occupancy-qualification-"
+
+_METHOD_SCHEMA: Final = "missioncore.laboratory-method/v1"
+_AUTHORITY: Final = {
+    "mode": "replay-simulated",
+    "physical_live": False,
+    "commands_enabled": False,
+    "actuation_allowed": False,
+    "navigation_or_safety_accepted": False,
+}
+
+
+class M48StaticOccupancyQualificationError(RuntimeError):
+    """The static-occupancy source, method, or immutable result is invalid."""
+
+
+@dataclass(frozen=True, slots=True)
+class M48StaticOccupancyQualificationResult:
+    result_id: str
+    result_root: Path
+    manifest: dict[str, Any]
+    report: dict[str, Any]
+    cases: tuple[dict[str, Any], ...]
+    canonical_anchors: tuple[dict[str, Any], ...]
+
+
+def build_m48_static_occupancy_qualification(
+    *,
+    repository_root: Path,
+    profile_path: Path,
+    m47_lab_root: Path,
+    graph_result_root: Path,
+    small_static_result_root: Path,
+    output_root: Path,
+    run_created_at_utc: str | None = None,
+) -> M48StaticOccupancyQualificationResult:
+    """Publish one deterministic, append-only M4.8R2 qualification result."""
+
+    repository = repository_root.resolve(strict=True)
+    profile_bytes, profile = _read_profile(profile_path)
+    source = _object(profile["source"], "M4.8R2 source")
+    try:
+        m47 = read_m47_reference_graph_lab(m47_lab_root)
+        small_static = read_m48_small_static_passage_regression(small_static_result_root)
+    except (M47ReferenceGraphLabError, M48SmallStaticRegressionError) as exc:
+        raise M48StaticOccupancyQualificationError(
+            "accepted M4.7/M4.8R1 evidence is invalid"
+        ) from exc
+    if (
+        m47.result_id != source.get("m47_lab_result_id")
+        or small_static.result_id != source.get("small_static_result_id")
+        or m47.manifest.get("accepted") is not True
+        or m47.manifest.get("ground_truth") is not False
+    ):
+        raise M48StaticOccupancyQualificationError("M4.8R2 source identity changed")
+
+    anchors_path = small_static.result_root / "anchors.jsonl"
+    if _file_sha256(anchors_path) != source.get("small_static_anchors_sha256"):
+        raise M48StaticOccupancyQualificationError("M4.8R2 anchor ledger changed")
+
+    graph_root = graph_result_root.resolve(strict=True)
+    graph_manifest = _read_json(graph_root / "manifest.json", maximum=2 * 1024 * 1024)
+    frames_path = graph_root / "frames.jsonl"
+    graph_files = _object(graph_manifest.get("files"), "M4.8R2 graph files")
+    graph_frames = _object(graph_files.get("frames.jsonl"), "M4.8R2 graph frame artifact")
+    if (
+        graph_root.name != source.get("m47_graph_result_id")
+        or graph_manifest.get("result_id") != graph_root.name
+        or graph_manifest.get("accepted") is not True
+        or graph_frames.get("sha256") != source.get("m47_graph_frames_sha256")
+        or _file_sha256(frames_path) != source.get("m47_graph_frames_sha256")
+    ):
+        raise M48StaticOccupancyQualificationError("M4.8R2 graph binding changed")
+
+    selection = _object(profile["selection"], "M4.8R2 selection")
+    anchors = tuple(
+        row
+        for row in small_static.anchors
+        if row.get("motion") == selection.get("motion")
+        and row.get("requires_avoidance_or_clearance")
+        is selection.get("requires_avoidance_or_clearance")
+    )
+    if not anchors:
+        raise M48StaticOccupancyQualificationError("M4.8R2 selected no static anchors")
+    frame_rows = _selected_graph_frames(frames_path, {int(row["sequence"]) for row in anchors})
+    store = RecordedGeometryStore.from_repository(repository)
+    candidate = _object(profile["candidate"], "M4.8R2 candidate")
+    candidate_association = replace(
+        store.profile.association,
+        semantic_minimum_occupied_points=int(candidate["minimum_points"]),
+        semantic_minimum_occupied_voxels=int(candidate["minimum_voxels"]),
+        semantic_voxel_size_m=float(candidate["voxel_size_m"]),
+        depth_cluster_minimum_gap_m=float(candidate["depth_cluster_minimum_gap_m"]),
+        depth_cluster_gap_fraction=float(candidate["depth_cluster_gap_fraction"]),
+        spatial_cluster_radius_m=float(candidate["spatial_cluster_radius_m"]),
+    )
+
+    cases: list[dict[str, Any]] = []
+    for anchor in anchors:
+        sequence = int(anchor["sequence"])
+        graph_row = frame_rows[sequence]
+        frame = store.frame_for_index(sequence)
+        if frame is None or not frame.surface_valid:
+            raise M48StaticOccupancyQualificationError(
+                "selected M4.8R2 anchor lacks qualified current LiDAR"
+            )
+        projected = project_map_points_kb4(
+            frame.points_map,
+            position_map_xyz=frame.sensor_position_map,
+            orientation_map_from_lidar_xyzw=frame.sensor_orientation_xyzw,
+            profile=frame.projection,
+        )
+        bbox = _pixel_bbox(anchor["extent_xyxy"], frame.projection.width, frame.projection.height)
+        baseline = semantic_geometry_support(
+            bbox,
+            projected=projected,
+            frame_points_map=frame.points_map,
+            point_class=frame.point_class,
+            profile=store.profile.association,
+        )
+        step_candidates = store.point_step_candidates_for_frame(sequence)
+        if step_candidates is None:
+            raise M48StaticOccupancyQualificationError(
+                "selected M4.8R2 anchor lacks low-step evidence"
+            )
+        union_classes = np.array(frame.point_class, copy=True)
+        union_classes[step_candidates > 0] = POINT_OCCUPIED
+        additive = semantic_geometry_support(
+            bbox,
+            projected=projected,
+            frame_points_map=frame.points_map,
+            point_class=union_classes,
+            profile=candidate_association,
+        )
+        graph_matches = _graph_component_matches(
+            graph_row=graph_row,
+            frame=frame,
+            bbox=bbox,
+            voxel_size_m=0.45,
+        )
+        raw_depths = _depths_in_bbox(projected.pixels_xy, projected.depths_m, bbox)
+        distance = _support_distance(
+            additive.occupied_depths_m, baseline.occupied_depths_m, raw_depths
+        )
+        band = _distance_band(distance, _object(profile["distance_bands_m"], "distance bands"))
+        accepted_graph = bool(graph_matches)
+        baseline_qualified = bool(baseline.qualified or accepted_graph)
+        candidate_qualified = bool(additive.qualified or accepted_graph)
+        false_free = graph_row["obstacle_map"].get("free_space_claimed") is True
+        cases.append(
+            {
+                "schema_version": M48_STATIC_OCCUPANCY_CASE_SCHEMA,
+                "anchor_id": anchor["anchor_id"],
+                "clip_id": anchor["clip_id"],
+                "sequence": sequence,
+                "extent_xyxy": anchor["extent_xyxy"],
+                "distance_m": distance,
+                "distance_band": band,
+                "accepted_graph": {
+                    "matched": accepted_graph,
+                    "component_count": len(graph_matches),
+                    "components": graph_matches,
+                    "free_space_claimed": false_free,
+                },
+                "current_local_surface": _support_projection(baseline),
+                "additive_step_candidate": _support_projection(additive),
+                "baseline_qualified": baseline_qualified,
+                "candidate_qualified": candidate_qualified,
+                "outcome": (
+                    "candidate-qualified"
+                    if candidate_qualified
+                    else "unresolved-unknown-never-free"
+                ),
+                "authority": "operator-assisted-development-anchor-not-truth",
+            }
+        )
+    cases.sort(key=lambda row: (int(row["sequence"]), str(row["anchor_id"])))
+
+    visual_report = _read_json(
+        m47.result_root / "visual-report.json",
+        maximum=2 * 1024 * 1024,
+    )
+    canonical = _canonical_anchors(visual_report, selection)
+    metrics = _metrics(cases, canonical)
+    acceptance = _object(profile["acceptance"], "M4.8R2 acceptance")
+    gates = {
+        "critical_near_candidate_recall": (
+            metrics["critical_near_candidate_recall"]
+            >= float(acceptance["minimum_critical_near_candidate_recall"])
+        ),
+        "approach_candidate_recall": (
+            metrics["approach_candidate_recall"]
+            >= float(acceptance["minimum_approach_candidate_recall"])
+        ),
+        "canonical_engineering_recall": (
+            metrics["canonical_engineering_recall"]
+            >= float(acceptance["minimum_canonical_engineering_recall"])
+        ),
+        "zero_false_free": metrics["false_free_count"]
+        <= int(acceptance["maximum_false_free_count"]),
+        "independent_truth_available": False,
+    }
+    near_ready = bool(
+        gates["critical_near_candidate_recall"]
+        and gates["canonical_engineering_recall"]
+        and gates["zero_false_free"]
+    )
+    accepted = bool(near_ready and gates["approach_candidate_recall"])
+    created_at = _utc_timestamp(run_created_at_utc or datetime.now(UTC).isoformat())
+    profile_sha256 = hashlib.sha256(profile_bytes).hexdigest()
+    producer_sha256 = _file_sha256(Path(__file__).resolve())
+    identity = {
+        "schema_version": M48_STATIC_OCCUPANCY_RESULT_SCHEMA,
+        "human_lab_id": profile["human_lab_id"],
+        "run_label": profile["run_label"],
+        "run_created_at_utc": created_at,
+        "pipeline_id": profile["pipeline_id"],
+        "experiment_id": profile["experiment_id"],
+        "profile_id": profile["profile_id"],
+        "profile_sha256": profile_sha256,
+        "producer_sha256": producer_sha256,
+        "source": source,
+        "selection": {
+            "operator_static_anchor_count": len(cases),
+            "canonical_engineering_anchor_count": len(canonical),
+        },
+        "authority": dict(_AUTHORITY),
+    }
+    result_id = M48_STATIC_OCCUPANCY_PREFIX + _canonical_sha256(identity)
+    method = {
+        "schema_version": _METHOD_SCHEMA,
+        "completeness": "complete",
+        "execution_class": "deterministic",
+        "pipeline_id": profile["pipeline_id"],
+        "components": [
+            {
+                "kind": "source",
+                "name": "accepted M4.7 current/rolling obstacle graph",
+                "version": source["m47_graph_result_id"],
+                "role": "immutable baseline occupied/unknown and threat decisions",
+                "identity_sha256": source["m47_graph_frames_sha256"],
+            },
+            {
+                "kind": "source",
+                "name": "M4.8R1 operator-assisted static anchors",
+                "version": source["small_static_result_id"],
+                "role": "candidate-visible diagnostic anchors; not independent truth",
+                "identity_sha256": source["small_static_anchors_sha256"],
+            },
+            {
+                "kind": "algorithm",
+                "name": "additive low-step static occupancy candidate",
+                "version": profile["profile_id"],
+                "role": "CPU-only occupied-or-unknown evidence; never clearing",
+                "identity_sha256": producer_sha256,
+            },
+        ],
+    }
+    report = {
+        "schema_version": M48_STATIC_OCCUPANCY_REPORT_SCHEMA,
+        "result_id": result_id,
+        "source": source,
+        "configuration": {
+            key: profile[key]
+            for key in (
+                "profile_id",
+                "pipeline_id",
+                "experiment_id",
+                "human_lab_id",
+                "run_label",
+                "distance_bands_m",
+                "candidate",
+                "acceptance",
+                "policy",
+            )
+        },
+        "method": method,
+        "metrics": metrics,
+        "gates": gates,
+        "decision": {
+            "state": "accepted-bounded-static-occupancy-qualification"
+            if accepted
+            else "partial-static-occupancy-qualification",
+            "critical_near_candidate_ready_for_shadow": near_ready,
+            "production_accepted": False,
+            "summary": (
+                "Accepted graph covers "
+                f"{metrics['baseline_qualified_count']}/{len(cases)} static assisted "
+                "anchors; the additive step candidate covers "
+                f"{metrics['candidate_qualified_count']}/{len(cases)}."
+            ),
+            "next_action": (
+                "Integrate the additive step evidence as an occupied-only Worker shadow, "
+                "then measure full replay FPS, occupancy growth and the unresolved 8-12 m "
+                "case."
+            ),
+        },
+        "limitations": [
+            (
+                "Operator-assisted anchors are candidate-visible development evidence, "
+                "not independent truth."
+            ),
+            "Projected camera rectangles do not define physical 3D colliders or chassis clearance.",
+            (
+                "The step candidate may add conservative false occupancy and therefore "
+                "requires a full replay load/volume shadow before cutover."
+            ),
+            (
+                "No ray clearing, planner-authoritative free space, physical navigation, "
+                "command, actuation or collision-safety authority is granted."
+            ),
+        ],
+        "authority": dict(_AUTHORITY),
+    }
+    destination = output_root.resolve(strict=False) / result_id
+    _publish_result(destination, identity, created_at, accepted, report, tuple(cases), canonical)
+    return read_m48_static_occupancy_qualification(destination)
+
+
+def read_m48_static_occupancy_qualification(
+    result_root: Path,
+) -> M48StaticOccupancyQualificationResult:
+    if result_root.is_symlink():
+        raise M48StaticOccupancyQualificationError("M4.8R2 result root is invalid")
+    root = result_root.resolve(strict=True)
+    if root.name.startswith(M48_STATIC_OCCUPANCY_PREFIX) is False:
+        raise M48StaticOccupancyQualificationError("M4.8R2 result root is invalid")
+    manifest = _read_json(root / "manifest.json", maximum=2 * 1024 * 1024)
+    report = _read_json(root / "report.json", maximum=4 * 1024 * 1024)
+    cases = tuple(_read_jsonl(root / "cases.jsonl"))
+    canonical = tuple(_read_jsonl(root / "canonical-anchors.jsonl"))
+    if (
+        manifest.get("schema_version") != M48_STATIC_OCCUPANCY_RESULT_SCHEMA
+        or manifest.get("result_id") != root.name
+        or report.get("schema_version") != M48_STATIC_OCCUPANCY_REPORT_SCHEMA
+        or report.get("result_id") != root.name
+        or manifest.get("ground_truth") is not False
+        or manifest.get("authority") != _AUTHORITY
+    ):
+        raise M48StaticOccupancyQualificationError("M4.8R2 result identity changed")
+    identity = _object(manifest.get("identity"), "M4.8R2 identity")
+    identity_sha256 = _canonical_sha256(identity)
+    if root.name != M48_STATIC_OCCUPANCY_PREFIX + identity_sha256:
+        raise M48StaticOccupancyQualificationError("M4.8R2 result identity changed")
+    artifacts = manifest.get("artifacts")
+    if not isinstance(artifacts, list):
+        raise M48StaticOccupancyQualificationError("M4.8R2 artifact proof changed")
+    artifact_paths = [
+        str(_object(item, "M4.8R2 artifact").get("path")) for item in artifacts
+    ]
+    if sorted(artifact_paths) != [
+        "canonical-anchors.jsonl",
+        "cases.jsonl",
+        "report.json",
+    ]:
+        raise M48StaticOccupancyQualificationError("M4.8R2 artifact proof changed")
+    for artifact in artifacts:
+        item = _object(artifact, "M4.8R2 artifact")
+        path = root / str(item.get("path"))
+        if path.parent != root or _file_sha256(path) != item.get("sha256"):
+            raise M48StaticOccupancyQualificationError("M4.8R2 artifact proof changed")
+    if manifest.get("identity_sha256") != identity_sha256:
+        raise M48StaticOccupancyQualificationError("M4.8R2 identity digest changed")
+    if not cases or any(
+        row.get("schema_version") != M48_STATIC_OCCUPANCY_CASE_SCHEMA for row in cases
+    ):
+        raise M48StaticOccupancyQualificationError("M4.8R2 case ledger changed")
+    if any(
+        row.get("schema_version") != M48_STATIC_OCCUPANCY_CANONICAL_SCHEMA
+        for row in canonical
+    ):
+        raise M48StaticOccupancyQualificationError("M4.8R2 canonical ledger changed")
+    return M48StaticOccupancyQualificationResult(
+        root.name, root, manifest, report, cases, canonical
+    )
+
+
+def _support_projection(value: Any) -> dict[str, object]:
+    depths = value.occupied_depths_m
+    return {
+        "qualified": bool(value.qualified),
+        "projected_point_count": int(value.projected_points_in_region),
+        "occupied_point_count": int(value.occupied_points_in_region),
+        "clustered_occupied_point_count": int(value.occupied_source_indices.size),
+        "nearest_depth_m": None if not depths.size else round(float(np.min(depths)), 6),
+        "median_depth_m": None if not depths.size else round(float(np.median(depths)), 6),
+    }
+
+
+def _graph_component_matches(
+    *,
+    graph_row: dict[str, Any],
+    frame: Any,
+    bbox: tuple[float, float, float, float],
+    voxel_size_m: float,
+) -> list[dict[str, object]]:
+    obstacle_map = _object(graph_row.get("obstacle_map"), "M4.8R2 obstacle map")
+    threats = {
+        str(row.get("component_id")): row
+        for row in graph_row.get("threats", [])
+        if isinstance(row, dict)
+    }
+    matches: list[dict[str, object]] = []
+    for obstacle in obstacle_map.get("occupied", []):
+        item = _object(obstacle, "M4.8R2 occupied component")
+        cells = item.get("cells")
+        if not isinstance(cells, list) or not cells:
+            continue
+        points = np.asarray(
+            [
+                [
+                    (int(cell["x"]) + 0.5) * voxel_size_m,
+                    (int(cell["y"]) + 0.5) * voxel_size_m,
+                    (int(cell["z"]) + 0.5) * voxel_size_m,
+                ]
+                for cell in cells
+            ],
+            dtype=np.float64,
+        )
+        projected = project_map_points_kb4(
+            points,
+            position_map_xyz=frame.sensor_position_map,
+            orientation_map_from_lidar_xyzw=frame.sensor_orientation_xyzw,
+            profile=frame.projection,
+        )
+        depths = _depths_in_bbox(projected.pixels_xy, projected.depths_m, bbox)
+        if not depths.size:
+            continue
+        component_id = str(item.get("component_id"))
+        assessment = _object(threats.get(component_id), "M4.8R2 threat assessment")
+        matches.append(
+            {
+                "component_id": component_id,
+                "state": item.get("state"),
+                "decision": assessment.get("decision"),
+                "projected_cell_count": int(depths.size),
+                "nearest_depth_m": round(float(np.min(depths)), 6),
+            }
+        )
+    matches.sort(key=lambda row: (float(row["nearest_depth_m"]), str(row["component_id"])))
+    return matches
+
+
+def _canonical_anchors(
+    report: dict[str, Any], selection: dict[str, Any]
+) -> tuple[dict[str, Any], ...]:
+    metrics = _object(report.get("metrics"), "M4.7 visual metrics")
+    visual = _object(metrics.get("visual_evidence"), "M4.7 visual evidence")
+    rows: list[dict[str, Any]] = []
+    for sequence in selection.get("canonical_engineering_sequences", []):
+        regression = _object(
+            visual.get(f"frame_{sequence}_regression"),
+            "canonical regression",
+        )
+        for anchor in regression.get("engineering_anchors", []):
+            item = _object(anchor, "canonical anchor")
+            rows.append(
+                {
+                    "schema_version": M48_STATIC_OCCUPANCY_CANONICAL_SCHEMA,
+                    "sequence": int(sequence),
+                    "anchor_id": item.get("anchor_id"),
+                    "matched": item.get("matched") is True,
+                    "decision": item.get("decision"),
+                    "must_assert_threat": item.get("must_assert_threat") is True,
+                    "authority": "camera-reviewed-engineering-anchor-not-truth",
+                }
+            )
+    return tuple(rows)
+
+
+def _metrics(
+    cases: list[dict[str, Any]], canonical: tuple[dict[str, Any], ...]
+) -> dict[str, object]:
+    def band_rows(name: str) -> list[dict[str, Any]]:
+        return [row for row in cases if row["distance_band"] == name]
+
+    def rate(rows: list[dict[str, Any]], key: str) -> float:
+        if not rows:
+            return 0.0
+        return sum(bool(row[key]) for row in rows) / len(rows)
+
+    near = band_rows("critical-near")
+    approach = band_rows("approach")
+    return {
+        "operator_static_anchor_count": len(cases),
+        "baseline_qualified_count": sum(bool(row["baseline_qualified"]) for row in cases),
+        "candidate_qualified_count": sum(bool(row["candidate_qualified"]) for row in cases),
+        "unresolved_unknown_count": sum(not bool(row["candidate_qualified"]) for row in cases),
+        "critical_near_anchor_count": len(near),
+        "critical_near_baseline_recall": rate(near, "baseline_qualified"),
+        "critical_near_candidate_recall": rate(near, "candidate_qualified"),
+        "approach_anchor_count": len(approach),
+        "approach_baseline_recall": rate(approach, "baseline_qualified"),
+        "approach_candidate_recall": rate(approach, "candidate_qualified"),
+        "canonical_engineering_anchor_count": len(canonical),
+        "canonical_engineering_recall": sum(bool(row["matched"]) for row in canonical)
+        / len(canonical)
+        if canonical
+        else 0.0,
+        "false_free_count": sum(bool(row["accepted_graph"]["free_space_claimed"]) for row in cases),
+        "independent_truth": False,
+    }
+
+
+def _selected_graph_frames(path: Path, sequences: set[int]) -> dict[int, dict[str, Any]]:
+    rows: dict[int, dict[str, Any]] = {}
+    with path.open("r", encoding="utf-8") as stream:
+        for line in stream:
+            row = _object(json.loads(line), "M4.8R2 graph frame")
+            sequence = row.get("sequence")
+            if isinstance(sequence, int) and sequence in sequences:
+                rows[sequence] = row
+            if len(rows) == len(sequences):
+                break
+    if set(rows) != sequences:
+        raise M48StaticOccupancyQualificationError("M4.8R2 graph frames are incomplete")
+    return rows
+
+
+def _pixel_bbox(value: object, width: int, height: int) -> tuple[float, float, float, float]:
+    extent = value if isinstance(value, list) else None
+    if extent is None or len(extent) != 4:
+        raise M48StaticOccupancyQualificationError("M4.8R2 anchor extent is invalid")
+    return (
+        float(extent[0]) * width,
+        float(extent[1]) * height,
+        float(extent[2]) * width,
+        float(extent[3]) * height,
+    )
+
+
+def _depths_in_bbox(
+    pixels: np.ndarray, depths: np.ndarray, bbox: tuple[float, float, float, float]
+) -> np.ndarray:
+    if not pixels.size:
+        return np.empty(0, dtype=np.float64)
+    inside = (
+        (pixels[:, 0] >= bbox[0])
+        & (pixels[:, 0] <= bbox[2])
+        & (pixels[:, 1] >= bbox[1])
+        & (pixels[:, 1] <= bbox[3])
+    )
+    return depths[inside]
+
+
+def _support_distance(*values: np.ndarray) -> float:
+    for value in values:
+        if value.size:
+            return round(float(np.median(value)), 6)
+    raise M48StaticOccupancyQualificationError("M4.8R2 anchor has no projected LiDAR depth")
+
+
+def _distance_band(distance: float, bands: dict[str, Any]) -> str:
+    for key, label in (("critical_near", "critical-near"), ("approach", "approach")):
+        bounds = bands.get(key)
+        if (
+            isinstance(bounds, list)
+            and len(bounds) == 2
+            and float(bounds[0]) <= distance < float(bounds[1])
+        ):
+            return label
+    return "outside-qualified-bands"
+
+
+def _read_profile(path: Path) -> tuple[bytes, dict[str, Any]]:
+    encoded = path.resolve(strict=True).read_bytes()
+    profile = _object(json.loads(encoded), "M4.8R2 profile")
+    if (
+        profile.get("schema_version") != M48_STATIC_OCCUPANCY_PROFILE_SCHEMA
+        or profile.get("authority") != _AUTHORITY
+    ):
+        raise M48StaticOccupancyQualificationError("M4.8R2 profile is invalid")
+    return encoded, profile
+
+
+def _publish_result(
+    destination: Path,
+    identity: dict[str, Any],
+    created_at: str,
+    accepted: bool,
+    report: dict[str, Any],
+    cases: tuple[dict[str, Any], ...],
+    canonical: tuple[dict[str, Any], ...],
+) -> None:
+    destination.parent.mkdir(mode=0o700, parents=True, exist_ok=True)
+    staging = destination.parent / f".{destination.name}.{uuid.uuid4().hex}.tmp"
+    staging.mkdir(mode=0o700)
+    try:
+        _write_json(staging / "report.json", report)
+        _write_jsonl(staging / "cases.jsonl", cases)
+        _write_jsonl(staging / "canonical-anchors.jsonl", canonical)
+        artifacts = [
+            _artifact(staging / name, role)
+            for name, role in (
+                ("cases.jsonl", "operator-static-anchor-comparisons"),
+                ("canonical-anchors.jsonl", "accepted-canonical-engineering-anchors"),
+                ("report.json", "m48-static-occupancy-report"),
+            )
+        ]
+        manifest = {
+            "schema_version": M48_STATIC_OCCUPANCY_RESULT_SCHEMA,
+            "result_id": destination.name,
+            "identity_sha256": _canonical_sha256(identity),
+            "identity": identity,
+            "created_at_utc": created_at,
+            "accepted": accepted,
+            "ground_truth": False,
+            "authority": dict(_AUTHORITY),
+            "artifacts": artifacts,
+        }
+        _write_json(staging / "manifest.json", manifest)
+        if destination.exists():
+            existing = {
+                path.name: _file_sha256(path) for path in destination.iterdir() if path.is_file()
+            }
+            proposed = {
+                path.name: _file_sha256(path) for path in staging.iterdir() if path.is_file()
+            }
+            if existing != proposed:
+                raise M48StaticOccupancyQualificationError("immutable M4.8R2 identity collided")
+            shutil.rmtree(staging)
+            return
+        os.replace(staging, destination)
+    except BaseException:
+        shutil.rmtree(staging, ignore_errors=True)
+        raise
+
+
+def _artifact(path: Path, role: str) -> dict[str, object]:
+    return {
+        "path": path.name,
+        "role": role,
+        "byte_length": path.stat().st_size,
+        "sha256": _file_sha256(path),
+        "media_type": "application/x-ndjson" if path.suffix == ".jsonl" else "application/json",
+    }
+
+
+def _read_json(path: Path, *, maximum: int) -> dict[str, Any]:
+    if path.is_symlink() or not path.is_file() or path.stat().st_size > maximum:
+        raise M48StaticOccupancyQualificationError(f"{path.name} is unavailable")
+    return _object(json.loads(path.read_text("utf-8")), path.name)
+
+
+def _read_jsonl(path: Path) -> list[dict[str, Any]]:
+    if path.is_symlink() or not path.is_file() or path.stat().st_size > 8 * 1024 * 1024:
+        raise M48StaticOccupancyQualificationError(f"{path.name} is unavailable")
+    return [
+        _object(json.loads(line), path.name)
+        for line in path.read_text("utf-8").splitlines()
+        if line.strip()
+    ]
+
+
+def _write_json(path: Path, value: object) -> None:
+    path.write_text(
+        json.dumps(value, ensure_ascii=False, sort_keys=True, indent=2) + "\n", encoding="utf-8"
+    )
+
+
+def _write_jsonl(path: Path, rows: tuple[dict[str, Any], ...]) -> None:
+    path.write_text(
+        "".join(
+            json.dumps(row, ensure_ascii=False, sort_keys=True, separators=(",", ":")) + "\n"
+            for row in rows
+        ),
+        encoding="utf-8",
+    )
+
+
+def _file_sha256(path: Path) -> str:
+    digest = hashlib.sha256()
+    with path.open("rb") as stream:
+        for chunk in iter(lambda: stream.read(1024 * 1024), b""):
+            digest.update(chunk)
+    return digest.hexdigest()
+
+
+def _canonical_sha256(value: object) -> str:
+    return hashlib.sha256(
+        json.dumps(value, ensure_ascii=False, sort_keys=True, separators=(",", ":")).encode("utf-8")
+    ).hexdigest()
+
+
+def _object(value: object, label: str) -> dict[str, Any]:
+    if not isinstance(value, dict):
+        raise M48StaticOccupancyQualificationError(f"{label} is invalid")
+    return value
+
+
+def _utc_timestamp(value: str) -> str:
+    parsed = datetime.fromisoformat(value.replace("Z", "+00:00"))
+    if parsed.tzinfo is None:
+        raise M48StaticOccupancyQualificationError("M4.8R2 creation time is invalid")
+    return parsed.astimezone(UTC).isoformat().replace("+00:00", "Z")
+
+
+__all__ = [
+    "M48StaticOccupancyQualificationError",
+    "M48StaticOccupancyQualificationResult",
+    "build_m48_static_occupancy_qualification",
+    "read_m48_static_occupancy_qualification",
+]

src/k1link/laboratory/m48q_native_risk_quality_lab.py

@@ -0,0 +1,471 @@
+"""Seal native raw-fisheye M4.8Q risk review evidence as a terminal LAB phase."""
+
+from __future__ import annotations
+
+import hashlib
+import json
+import re
+import shutil
+import tempfile
+from dataclasses import dataclass
+from datetime import UTC, datetime
+from pathlib import Path
+from typing import Any, Final
+
+from k1link.perception.fixed_class_detector_tournament import (
+    canonical_json,
+    false_authority,
+    sha256_path,
+)
+
+LAB_SCHEMA: Final = "missioncore.m48q-native-risk-quality-lab/v1"
+REPORT_SCHEMA: Final = "missioncore.m48q-native-risk-quality-report/v1"
+CATALOG_SCHEMA: Final = "missioncore.m48q-native-risk-review-catalog/v1"
+CASE_SCHEMA: Final = "missioncore.m48q-native-risk-review-case/v1"
+RESULT_PREFIX: Final = "m48q-native-risk-quality-lab-"
+PROFILE_RELATIVE_PATH: Final = Path("config/perception/m48q-native-risk-case-mining-v1.json")
+DETECTOR_PROFILE_RELATIVE_PATH: Final = Path(
+    "config/perception/rf-detr-large-native-kb4-risk-shadow-v0.json"
+)
+WORKER_RELATIVE_ROOT: Final = Path(
+    ".runtime/worker-results/m48q-native-risk-case-mining/ravnoves00-native-raw-review-v3"
+)
+EXPECTED_PROFILE_SHA256: Final = "c455055e63578d505edc80b66d67e795916a3d0297cc18bfee5a6af7b032ceda"
+EXPECTED_DETECTOR_PROFILE_SHA256: Final = (
+    "dbf4da5dbad6c3c22b1280b46ffcad81719bd183c81c263a4859847d829019b6"
+)
+EXPECTED_WORKER_RESULT_SHA256: Final = (
+    "a8f98d6d68abd6fd627caa05aaa3f048d69279a989b07fc2552b508af909a623"
+)
+EXPECTED_CASES_SHA256: Final = "9cea2a4a4558d761bc76b0d70474673ff07210473f53bd32cf178e8e0c8e179c"
+EXPECTED_REPORT_IDENTITY_SHA256: Final = (
+    "b744775c0e08d18d728f04021cd2acf9b1ed6fcacf1520352ee04e06a6d5d324"
+)
+CASE_ID: Final = re.compile(r"^[0-9]{6}$")
+
+
+class M48QNativeRiskQualityLabError(RuntimeError):
+    """Raised when native M4.8Q evidence cannot be sealed honestly."""
+
+
+@dataclass(frozen=True, slots=True)
+class M48QNativeRiskQualityLabResult:
+    result_root: Path
+    result_id: str
+    manifest: dict[str, Any]
+
+
+def build_m48q_native_risk_quality_lab(
+    *,
+    repository_root: Path,
+    output_root: Path,
+) -> M48QNativeRiskQualityLabResult:
+    repository = repository_root.expanduser().resolve(strict=True)
+    profile_path = repository / PROFILE_RELATIVE_PATH
+    detector_profile_path = repository / DETECTOR_PROFILE_RELATIVE_PATH
+    worker_root = repository / WORKER_RELATIVE_ROOT
+    worker_result_path = worker_root / "result.json"
+    cases_path = worker_root / "cases.jsonl"
+    images_root = worker_root / "cases"
+    for path in (
+        profile_path,
+        detector_profile_path,
+        worker_result_path,
+        cases_path,
+    ):
+        if path.is_symlink() or not path.is_file():
+            raise M48QNativeRiskQualityLabError(f"required M4.8Q evidence is missing: {path.name}")
+    if images_root.is_symlink() or not images_root.is_dir():
+        raise M48QNativeRiskQualityLabError("M4.8Q image evidence is missing")
+    expected_hashes = {
+        profile_path: EXPECTED_PROFILE_SHA256,
+        detector_profile_path: EXPECTED_DETECTOR_PROFILE_SHA256,
+        worker_result_path: EXPECTED_WORKER_RESULT_SHA256,
+        cases_path: EXPECTED_CASES_SHA256,
+    }
+    if any(sha256_path(path) != expected for path, expected in expected_hashes.items()):
+        raise M48QNativeRiskQualityLabError("M4.8Q source evidence identity changed")
+
+    profile = _read_object(profile_path)
+    detector_profile = _read_object(detector_profile_path)
+    worker_result = _read_object(worker_result_path)
+    cases = _read_cases(cases_path)
+    _validate_inputs(
+        profile=profile,
+        detector_profile=detector_profile,
+        worker_result=worker_result,
+        cases=cases,
+        images_root=images_root,
+    )
+    method = _method(profile, detector_profile, worker_result)
+    identity = {
+        "schema_version": LAB_SCHEMA,
+        "profile": {
+            "profile_id": profile["profile_id"],
+            "sha256": EXPECTED_PROFILE_SHA256,
+        },
+        "detector_profile": {
+            "profile_id": detector_profile["profile_id"],
+            "sha256": EXPECTED_DETECTOR_PROFILE_SHA256,
+        },
+        "source": {
+            "source_id": "RAVNOVES00",
+            "video_sha256": profile["source"]["video_sha256"],
+            "graph_result_sha256": worker_result["source"]["graph_result_sha256"],
+            "graph_frames_sha256": worker_result["source"]["graph_frames_sha256"],
+            "comparison_result_sha256": worker_result["source"]["comparison_result_sha256"],
+            "comparison_frames_sha256": worker_result["source"]["comparison_frames_sha256"],
+            "worker_result_sha256": EXPECTED_WORKER_RESULT_SHA256,
+            "cases_sha256": EXPECTED_CASES_SHA256,
+        },
+        "method": method,
+        "authority": false_authority(),
+    }
+    identity_sha256 = hashlib.sha256(canonical_json(identity)).hexdigest()
+    result_id = RESULT_PREFIX + identity_sha256
+    root = output_root.expanduser().absolute()
+    root.mkdir(mode=0o700, parents=True, exist_ok=True)
+    destination = root / result_id
+    if destination.exists():
+        manifest = _read_object(destination / "manifest.json")
+        if (
+            manifest.get("schema_version") != LAB_SCHEMA
+            or manifest.get("identity_sha256") != identity_sha256
+            or manifest.get("result_id") != result_id
+        ):
+            raise M48QNativeRiskQualityLabError("existing M4.8Q LAB identity conflicts")
+        return M48QNativeRiskQualityLabResult(destination, result_id, manifest)
+
+    created_at_utc = datetime.now(UTC).isoformat(timespec="microseconds").replace("+00:00", "Z")
+    temporary = Path(tempfile.mkdtemp(prefix=".m48q-native-risk-lab-", dir=root))
+    try:
+        (temporary / "cases").mkdir(mode=0o700)
+        shutil.copyfile(profile_path, temporary / "profile.json")
+        shutil.copyfile(detector_profile_path, temporary / "detector-profile.json")
+        shutil.copyfile(worker_result_path, temporary / "worker-result.json")
+        shutil.copyfile(cases_path, temporary / "cases.jsonl")
+
+        catalog_cases: list[dict[str, object]] = []
+        for case in cases:
+            image = case["image"]
+            source_image = worker_root / image["path"]
+            destination_image = temporary / image["path"]
+            shutil.copyfile(source_image, destination_image)
+            catalog_cases.append(
+                {
+                    "case_id": case["case_id"],
+                    "sequence": case["sequence"],
+                    "frame_id": case["frame_id"],
+                    "evidence_time_ns": case["evidence_time_ns"],
+                    "path": image["path"],
+                    "media_type": "image/jpeg",
+                    "width": 800,
+                    "height": 600,
+                    "byte_length": destination_image.stat().st_size,
+                    "sha256": sha256_path(destination_image),
+                    "geometric_resampling": False,
+                    "selection_buckets": case["selection_buckets"],
+                    "comparison": case["comparison"],
+                    "proposals": case["proposals"],
+                }
+            )
+        catalog = {
+            "schema_version": CATALOG_SCHEMA,
+            "result_id": result_id,
+            "case_count": len(catalog_cases),
+            "source_raster": {"width": 800, "height": 600},
+            "overlay": {
+                "client_rendered": True,
+                "toggleable": True,
+                "box_coordinates": "source-pixel-xyxy",
+                "class_names": True,
+                "scores": True,
+            },
+            "ground_truth": False,
+            "cases": catalog_cases,
+        }
+        catalog_path = temporary / "catalog.json"
+        catalog_path.write_bytes(canonical_json(catalog) + b"\n")
+
+        graph_qualification = detector_profile["qualification"][
+            "full_ravnoves00_integrated_reference_graph"
+        ]
+        decision = {
+            "review_ready": True,
+            "quality_evaluated": False,
+            "ground_truth": False,
+            "candidate_accepted": False,
+            "production_accepted": False,
+            "next_action": "operator-adjudication-in-existing-m48-review-instrument",
+        }
+        report = {
+            "schema_version": REPORT_SCHEMA,
+            "result_id": result_id,
+            "source": {
+                **profile["source"],
+                "graph_result_sha256": worker_result["source"]["graph_result_sha256"],
+                "graph_frames_sha256": worker_result["source"]["graph_frames_sha256"],
+                "independent_route_truth_available": False,
+            },
+            "configuration": {
+                "candidate": profile["candidate"],
+                "selection": profile["selection"],
+            },
+            "method": method,
+            "execution": {
+                "worker": worker_result["worker"],
+                "full_graph_frames": graph_qualification["frame_count"],
+                "requested_source_rate_hz": graph_qualification["requested_source_rate_hz"],
+                "effective_world_state_fps": graph_qualification["effective_world_state_fps"],
+                "world_state_completion_p95_ms": graph_qualification[
+                    "world_state_completion_p95_ms"
+                ],
+                "detector_total_p95_ms": graph_qualification["detector_total_p95_ms"],
+                "gpu_utilization_p95_percent": graph_qualification["gpu_utilization_p95_percent"],
+                "gpu_memory_used_maximum_mib": graph_qualification["gpu_memory_used_maximum_mib"],
+                "additional_inference_passes": 0,
+            },
+            "metrics": {
+                "selection": worker_result["selection"],
+                "runtime": {
+                    "delivery_ratio": graph_qualification["delivery_ratio"],
+                    "integrated_runtime_gate_passed": graph_qualification[
+                        "integrated_runtime_gate_passed"
+                    ],
+                    "operating_target_gate_passed": graph_qualification[
+                        "operating_target_gate_passed"
+                    ],
+                },
+                "native_tensor_parity": detector_profile["qualification"][
+                    "native_pytorch_tensorrt_parity"
+                ],
+                "native_vs_legacy_704": detector_profile["qualification"][
+                    "full_ravnoves00_native_vs_legacy_704"
+                ],
+            },
+            "acceptance": {
+                "review_ready": True,
+                "integrated_runtime_gate_passed": True,
+                "independent_quality_evaluated": False,
+                "semantic_candidate_accepted": False,
+            },
+            "decision": decision,
+            "limitations": worker_result["limitations"],
+            "authority": false_authority(),
+            "visual_evidence": {
+                "kind": "native-raw-fisheye-risk-case-review",
+                "case_count": 24,
+                "source_raster": "800x600",
+                "geometric_resampling": False,
+                "boxes_baked_into_images": False,
+                "ground_truth": False,
+            },
+        }
+        report_path = temporary / "report.json"
+        report_path.write_bytes(canonical_json(report) + b"\n")
+        artifacts = _artifact_manifest(temporary)
+        manifest = {
+            "schema_version": LAB_SCHEMA,
+            "result_id": result_id,
+            "identity_sha256": identity_sha256,
+            "identity": identity,
+            "created_at_utc": created_at_utc,
+            "status": "complete-review-ready-quality-not-adjudicated",
+            "completed": True,
+            "bounded_question_accepted": True,
+            "ground_truth": False,
+            "method": method,
+            "metrics": report["metrics"],
+            "decision": decision,
+            "limitations": worker_result["limitations"],
+            "authority": false_authority(),
+            "artifacts": artifacts,
+        }
+        (temporary / "manifest.json").write_bytes(canonical_json(manifest) + b"\n")
+        temporary.replace(destination)
+    except BaseException:
+        shutil.rmtree(temporary, ignore_errors=True)
+        raise
+    return M48QNativeRiskQualityLabResult(destination, result_id, manifest)
+
+
+def _validate_inputs(
+    *,
+    profile: dict[str, Any],
+    detector_profile: dict[str, Any],
+    worker_result: dict[str, Any],
+    cases: list[dict[str, Any]],
+    images_root: Path,
+) -> None:
+    if (
+        profile.get("schema_version") != "missioncore.m48q-native-risk-case-mining-profile/v1"
+        or profile.get("source", {}).get("geometric_resampling") is not False
+        or profile.get("source", {}).get("raster_width") != 800
+        or profile.get("source", {}).get("raster_height") != 600
+        or profile.get("authority") != false_authority()
+        or detector_profile.get("schema_version")
+        != "missioncore.rf-detr-native-risk-shadow-profile/v0"
+        or detector_profile.get("preprocessing", {}).get("resize") is not False
+        or detector_profile.get("preprocessing", {}).get("geometric_resampling") is not False
+        or detector_profile.get("status", {}).get("integrated_world_state_gate_passed") is not True
+        or worker_result.get("schema_version")
+        != "missioncore.m48q-native-risk-case-mining-result/v1"
+        or worker_result.get("status") != "complete-review-ready-quality-not-adjudicated"
+        or worker_result.get("completed") is not True
+        or worker_result.get("report_identity_sha256") != EXPECTED_REPORT_IDENTITY_SHA256
+        or worker_result.get("artifacts", {}).get("cases", {}).get("sha256")
+        != EXPECTED_CASES_SHA256
+        or worker_result.get("selection", {}).get("case_count") != 24
+        or worker_result.get("decision", {}).get("quality_evaluated") is not False
+        or worker_result.get("authority") != false_authority()
+        or len(cases) != 24
+        or len({case.get("case_id") for case in cases}) != 24
+    ):
+        raise M48QNativeRiskQualityLabError("M4.8Q evidence contract changed")
+    for case in cases:
+        image = case.get("image")
+        proposals = case.get("proposals")
+        if (
+            case.get("schema_version") != CASE_SCHEMA
+            or not isinstance(case.get("case_id"), str)
+            or CASE_ID.fullmatch(case["case_id"]) is None
+            or case.get("case_id") != f"{case.get('sequence'):06d}"
+            or case.get("frame_id") != f"frame-{case.get('sequence'):06d}"
+            or case.get("ground_truth") is not False
+            or case.get("quality_evaluated") is not False
+            or case.get("authority") != false_authority()
+            or not isinstance(image, dict)
+            or image.get("path") != f"cases/frame-{case['case_id']}.jpg"
+            or image.get("width") != 800
+            or image.get("height") != 600
+            or image.get("geometric_resampling") is not False
+            or not isinstance(proposals, list)
+            or not proposals
+        ):
+            raise M48QNativeRiskQualityLabError("M4.8Q review case contract changed")
+        image_path = images_root.parent / image["path"]
+        if (
+            image_path.is_symlink()
+            or not image_path.is_file()
+            or image_path.stat().st_size != image.get("byte_length")
+            or sha256_path(image_path) != image.get("sha256")
+        ):
+            raise M48QNativeRiskQualityLabError("M4.8Q review image proof changed")
+
+
+def _method(
+    profile: dict[str, Any],
+    detector_profile: dict[str, Any],
+    worker_result: dict[str, Any],
+) -> dict[str, object]:
+    return {
+        "schema_version": "missioncore.laboratory-method/v1",
+        "completeness": "complete",
+        "execution_class": "hybrid",
+        "pipeline_id": "m48q-native-raw-fisheye-risk-case-review/v1",
+        "components": [
+            {
+                "kind": "source",
+                "name": "RAVNOVES00 raw KB4 video",
+                "version": "800x600 immutable recording",
+                "role": "unrectified review raster",
+                "identity_sha256": profile["source"]["video_sha256"],
+            },
+            {
+                "kind": "model",
+                "name": "RF-DETR-L native KB4 TensorRT",
+                "version": profile["candidate"]["model_id"],
+                "role": "fixed-class behavior-risk shadow proposals",
+                "identity_sha256": profile["candidate"]["engine_sha256"],
+            },
+            {
+                "kind": "runtime",
+                "name": "M4.7 native reference graph",
+                "version": "full RAVNOVES00 at recorded 12 FPS",
+                "role": "proposal and realtime evidence source",
+                "identity_sha256": worker_result["source"]["graph_result_sha256"],
+            },
+            {
+                "kind": "algorithm",
+                "name": "bounded diagnostic case miner",
+                "version": profile["profile_id"],
+                "role": "deterministic risk-family and edge-case sampling",
+                "identity_sha256": worker_result["identity"]["runner_sha256"],
+            },
+            {
+                "kind": "tool",
+                "name": "M4.8 existing image-case review instrument",
+                "version": "client-rendered source-pixel overlay/v1",
+                "role": "operator review without baked boxes",
+                "identity_sha256": EXPECTED_CASES_SHA256,
+            },
+        ],
+    }
+
+
+def _artifact_manifest(root: Path) -> list[dict[str, object]]:
+    artifacts: list[dict[str, object]] = []
+    for path in sorted(item for item in root.rglob("*") if item.is_file()):
+        relative = path.relative_to(root).as_posix()
+        if relative == "manifest.json":
+            continue
+        media_type = "application/json"
+        schema_version: str | None = None
+        role = "supporting-evidence"
+        if relative == "report.json":
+            role = "laboratory-report"
+            schema_version = REPORT_SCHEMA
+        elif relative == "catalog.json":
+            role = "visual-evidence-catalog"
+            schema_version = CATALOG_SCHEMA
+        elif relative == "profile.json":
+            role = "predeclared-native-risk-review-profile"
+            schema_version = "missioncore.m48q-native-risk-case-mining-profile/v1"
+        elif relative == "detector-profile.json":
+            role = "qualified-native-detector-profile"
+            schema_version = "missioncore.rf-detr-native-risk-shadow-profile/v0"
+        elif relative == "worker-result.json":
+            role = "upstream-worker-case-mining-result"
+            schema_version = "missioncore.m48q-native-risk-case-mining-result/v1"
+        elif relative == "cases.jsonl":
+            media_type = "application/x-ndjson"
+            role = "native-risk-review-case-ledger"
+            schema_version = CASE_SCHEMA
+        elif relative.endswith(".jpg"):
+            media_type = "image/jpeg"
+            role = "visual-evidence-native-raw-fisheye-frame"
+        artifacts.append(
+            {
+                "role": role,
+                "path": relative,
+                "byte_length": path.stat().st_size,
+                "sha256": sha256_path(path),
+                "media_type": media_type,
+                "schema_version": schema_version,
+            }
+        )
+    return artifacts
+
+
+def _read_object(path: Path) -> dict[str, Any]:
+    try:
+        value: object = json.loads(path.read_text("utf-8"))
+    except (OSError, json.JSONDecodeError) as exc:
+        raise M48QNativeRiskQualityLabError(f"invalid JSON evidence: {path.name}") from exc
+    if not isinstance(value, dict):
+        raise M48QNativeRiskQualityLabError(f"JSON evidence must be an object: {path.name}")
+    return value
+
+
+def _read_cases(path: Path) -> list[dict[str, Any]]:
+    cases: list[dict[str, Any]] = []
+    try:
+        with path.open("r", encoding="utf-8") as stream:
+            for line in stream:
+                value: object = json.loads(line)
+                if not isinstance(value, dict):
+                    raise M48QNativeRiskQualityLabError("M4.8Q case ledger row is not an object")
+                cases.append(value)
+    except (OSError, json.JSONDecodeError) as exc:
+        raise M48QNativeRiskQualityLabError("M4.8Q case ledger cannot be read") from exc
+    return cases

src/k1link/perception/geometry.py

@@ -344,6 +344,28 @@ class RecordedGeometryStore:
         points.setflags(write=False)
         return points
 
+    def point_step_candidates_for_frame(self, frame_index: int) -> UInt8Array | None:
+        """Expose the sealed low-step diagnostic in the source point index space.
+
+        The array is evidence only: a non-zero value may add conservative
+        occupied/unknown support, but it never clears a cell or claims free
+        space.  Unavailable and surface-invalid frames remain unavailable.
+        """
+
+        frame = self.frame_for_index(frame_index)
+        if frame is None or not frame.surface_valid:
+            return None
+        offsets = self._source["cloud_offsets"]
+        start, end = int(offsets[frame_index]), int(offsets[frame_index + 1])
+        values = np.asarray(
+            self._surface["point_step_candidate"][start:end],
+            dtype=np.uint8,
+        )
+        if values.shape != (frame.source_point_count,):
+            raise GeometryProviderError("local-surface step evidence changed")
+        values.setflags(write=False)
+        return values
+
     @property
     def maximum_current_point_count(self) -> int:
         """Return the immutable source-pack upper bound for one recorded increment."""

src/k1link/web/app.py

@@ -153,8 +153,8 @@ from k1link.web.runtime_readiness import (
     build_runtime_readiness,
 )
 from k1link.web.session_api import build_session_router
-from k1link.web.simulation_world_provider_api import build_simulation_world_provider_router
 from k1link.web.simulation_projects_api import build_simulation_projects_router
+from k1link.web.simulation_world_provider_api import build_simulation_world_provider_router
 from k1link.web.system_telemetry_api import build_system_telemetry_router
 from k1link.web.viewer_diagnostics_api import build_viewer_diagnostics_router
 
@@ -934,6 +934,13 @@ app.include_router(
             / "m48"
             / "small-static-passage-regression-results"
         ),
+        static_occupancy_result_root_provider=lambda: (
+            REPOSITORY_ROOT
+            / ".runtime"
+            / "compute-experiments"
+            / "m48"
+            / "static-occupancy-qualification-results"
+        ),
         camera_frame_provider=(
             session_recorded_camera_frame_service.extract
             if session_recorded_camera_frame_service is not None
@@ -980,6 +987,13 @@ app.include_router(
             / "m48t-risk-quality"
             / "lab-results"
         ),
+        native_root_provider=lambda: (
+            REPOSITORY_ROOT
+            / ".runtime"
+            / "compute-experiments"
+            / "m48t-risk-quality"
+            / "native-lab-results"
+        ),
     )
 )
 app.include_router(

src/k1link/web/m48_object_quality_api.py

@@ -48,6 +48,11 @@ from k1link.laboratory.m48_small_static_regression import (
     M48SmallStaticRegressionResult,
     read_m48_small_static_passage_regression,
 )
+from k1link.laboratory.m48_static_occupancy_qualification import (
+    M48StaticOccupancyQualificationError,
+    M48StaticOccupancyQualificationResult,
+    read_m48_static_occupancy_qualification,
+)
 from k1link.sessions import RecordedCameraPlaybackSource
 
 _PACK_ID = re.compile(r"^m48-object-quality-pack-[a-f0-9]{64}$")
@@ -57,6 +62,9 @@ _SMALL_STATIC_RESULT_ID = re.compile(
     r"^m48-small-static-passage-regression-[a-f0-9]{64}$"
 )
 _SMALL_STATIC_ANCHOR_ID = re.compile(r"^anchor-[a-f0-9]{24}$")
+_STATIC_OCCUPANCY_RESULT_ID = re.compile(
+    r"^m48-static-occupancy-qualification-[a-f0-9]{64}$"
+)
 _M47_LAB_RESULT_ID = re.compile(r"^m47-reference-graph-lab-[a-f0-9]{64}$")
 _FAILURE_ID = re.compile(r"^m48-failure-[a-f0-9]{64}$")
 _REVIEW_SESSION_ID = re.compile(r"^m48-review-session-[a-f0-9]{64}$")
@@ -93,6 +101,12 @@ _SMALL_STATIC_CASE_CATALOG_SCHEMA: Final = (
 _SMALL_STATIC_CASE_VIEW_SCHEMA: Final = (
     "missioncore.m48-small-static-passage-regression-case-view/v1"
 )
+_STATIC_OCCUPANCY_RESULT_VIEW_SCHEMA: Final = (
+    "missioncore.m48-static-occupancy-qualification-result-view/v1"
+)
+_STATIC_OCCUPANCY_CASE_CATALOG_SCHEMA: Final = (
+    "missioncore.m48-static-occupancy-case-catalog/v1"
+)
 _FAILURE_ATLAS_VIEW_SCHEMA: Final = "missioncore.m48-object-quality-failure-atlas-view/v1"
 _FAILURE_CASE_VIEW_SCHEMA: Final = "missioncore.m48-object-quality-failure-case-view/v1"
 _REVIEW_CAPABILITY_HEADER: Final = "X-M48-Review-Capability"
@@ -438,6 +452,7 @@ def build_m48_object_quality_router(
     truth_root_provider: RootProvider = lambda: None,
     result_root_provider: RootProvider = lambda: None,
     small_static_result_root_provider: RootProvider = lambda: None,
+    static_occupancy_result_root_provider: RootProvider = lambda: None,
     camera_frame_provider: CameraFrameProvider | None = None,
     camera_playback_provider: CameraPlaybackProvider | None = None,
     spatial_evidence_provider: SpatialEvidenceProvider | None = None,
@@ -1593,6 +1608,56 @@ def build_m48_object_quality_router(
             "access": "assisted-development-regression-case-read-only",
         }
 
+    @router.get("/regressions/static-occupancy/{result_id}")
+    def get_static_occupancy_qualification(
+        result_id: Annotated[str, ApiPath(pattern=_STATIC_OCCUPANCY_RESULT_ID.pattern)],
+    ) -> dict[str, object]:
+        result = _resolve_static_occupancy_result(
+            static_occupancy_result_root_provider,
+            result_id,
+        )
+        source = _object(result.report.get("source"), "M4.8R2 source")
+        configuration = _object(
+            result.report.get("configuration"),
+            "M4.8R2 configuration",
+        )
+        return {
+            "schema_version": _STATIC_OCCUPANCY_RESULT_VIEW_SCHEMA,
+            "result_id": result.result_id,
+            "created_at_utc": result.manifest.get("created_at_utc"),
+            "reference_graph_lab_result_id": source.get("m47_lab_result_id"),
+            "small_static_result_id": source.get("small_static_result_id"),
+            "run_label": configuration.get("run_label"),
+            "pipeline_id": configuration.get("pipeline_id"),
+            "experiment_id": configuration.get("experiment_id"),
+            "accepted": result.manifest.get("accepted"),
+            "metrics": copy.deepcopy(result.report.get("metrics")),
+            "gates": copy.deepcopy(result.report.get("gates")),
+            "decision": copy.deepcopy(result.report.get("decision")),
+            "ground_truth": False,
+            "independent_truth": False,
+            "authority": dict(_AUTHORITY),
+            "access": "static-occupancy-qualification-read-only",
+        }
+
+    @router.get("/regressions/static-occupancy/{result_id}/cases")
+    def get_static_occupancy_qualification_cases(
+        result_id: Annotated[str, ApiPath(pattern=_STATIC_OCCUPANCY_RESULT_ID.pattern)],
+    ) -> dict[str, object]:
+        result = _resolve_static_occupancy_result(
+            static_occupancy_result_root_provider,
+            result_id,
+        )
+        return {
+            "schema_version": _STATIC_OCCUPANCY_CASE_CATALOG_SCHEMA,
+            "result_id": result.result_id,
+            "cases": copy.deepcopy(result.cases),
+            "case_count": len(result.cases),
+            "ground_truth": False,
+            "authority": dict(_AUTHORITY),
+            "access": "static-occupancy-qualification-read-only",
+        }
+
     return router
 
 
@@ -1691,6 +1756,27 @@ def _resolve_small_static_result(
         ) from None
 
 
+def _resolve_static_occupancy_result(
+    provider: RootProvider,
+    result_id: str,
+) -> M48StaticOccupancyQualificationResult:
+    if _STATIC_OCCUPANCY_RESULT_ID.fullmatch(result_id) is None:
+        raise HTTPException(status_code=404, detail="M4.8R2 result was not found")
+    root = _configured_root(provider)
+    if root is None:
+        raise HTTPException(status_code=404, detail="M4.8R2 result was not found")
+    path = root / result_id
+    if path.is_symlink() or not path.is_dir():
+        raise HTTPException(status_code=404, detail="M4.8R2 result was not found")
+    try:
+        resolved = path.resolve(strict=True)
+        if resolved.parent != root:
+            raise OSError("M4.8R2 result escaped root")
+        return read_m48_static_occupancy_qualification(resolved)
+    except (M48StaticOccupancyQualificationError, OSError, TypeError, ValueError):
+        raise HTTPException(status_code=404, detail="M4.8R2 result was not found") from None
+
+
 def _result_sources(
     result: M48ObjectQualityResult,
     *,

src/k1link/web/m48t_risk_quality_lab_api.py

@@ -1,4 +1,4 @@
-"""Read-only API for the sealed M4.8T quality and temporal LAB."""
+"""Read-only API for the M4.8T legacy quality and M4.8Q native review lifecycle."""
 
 from __future__ import annotations
 
@@ -8,7 +8,7 @@ import json
 import re
 from collections.abc import Callable
 from pathlib import Path, PurePosixPath
-from typing import Any, Final
+from typing import Any, Final, Literal
 
 from fastapi import APIRouter, HTTPException, Query
 from fastapi.responses import FileResponse
@@ -18,30 +18,61 @@ from k1link.laboratory.evidence_report import (
     LaboratoryEvidenceReportError,
     verify_laboratory_evidence_result,
 )
+from k1link.laboratory.m48q_native_risk_quality_lab import (
+    CATALOG_SCHEMA as NATIVE_CATALOG_SCHEMA,
+)
+from k1link.laboratory.m48q_native_risk_quality_lab import (
+    LAB_SCHEMA as NATIVE_LAB_SCHEMA,
+)
+from k1link.laboratory.m48q_native_risk_quality_lab import (
+    REPORT_SCHEMA as NATIVE_REPORT_SCHEMA,
+)
+from k1link.laboratory.m48q_native_risk_quality_lab import (
+    RESULT_PREFIX as NATIVE_RESULT_PREFIX,
+)
 from k1link.laboratory.m48t_risk_quality_lab import (
-    CATALOG_SCHEMA,
-    LAB_SCHEMA,
-    REPORT_SCHEMA,
-    RESULT_PREFIX,
+    CATALOG_SCHEMA as LEGACY_CATALOG_SCHEMA,
+)
+from k1link.laboratory.m48t_risk_quality_lab import (
+    LAB_SCHEMA as LEGACY_LAB_SCHEMA,
+)
+from k1link.laboratory.m48t_risk_quality_lab import (
+    REPORT_SCHEMA as LEGACY_REPORT_SCHEMA,
+)
+from k1link.laboratory.m48t_risk_quality_lab import (
+    RESULT_PREFIX as LEGACY_RESULT_PREFIX,
 )
 from k1link.perception.fixed_class_detector_tournament import false_authority
 
 RootProvider = Callable[[], Path | None]
-RESULT_ID: Final = re.compile(rf"^{re.escape(RESULT_PREFIX)}[a-f0-9]{{64}}$")
-CASE_ID: Final = re.compile(r"^[0-9]{12}$")
-VIEW_SCHEMA: Final = "missioncore.m48t-risk-quality-temporal-view/v1"
-CATALOG_VIEW_SCHEMA: Final = "missioncore.m48t-risk-quality-temporal-catalog/v1"
-_DEFINITION: Final = LaboratoryEvidenceDefinition(
+Variant = Literal["legacy", "native"]
+LEGACY_RESULT_ID: Final = re.compile(rf"^{re.escape(LEGACY_RESULT_PREFIX)}[a-f0-9]{{64}}$")
+NATIVE_RESULT_ID: Final = re.compile(rf"^{re.escape(NATIVE_RESULT_PREFIX)}[a-f0-9]{{64}}$")
+LEGACY_CASE_ID: Final = re.compile(r"^[0-9]{12}$")
+NATIVE_CASE_ID: Final = re.compile(r"^[0-9]{6}$")
+LEGACY_VIEW_SCHEMA: Final = "missioncore.m48t-risk-quality-temporal-view/v1"
+NATIVE_VIEW_SCHEMA: Final = "missioncore.m48q-native-risk-quality-view/v1"
+CATALOG_VIEW_SCHEMA: Final = "missioncore.m48t-risk-quality-lifecycle-catalog/v1"
+_LEGACY_DEFINITION: Final = LaboratoryEvidenceDefinition(
     work_id="m48t-risk-quality-temporal",
     runtime_relative_root=PurePosixPath("m48t-risk-quality/lab-results"),
     result_id_prefix="m48t-risk-quality-temporal-lab",
     document_name="manifest.json",
-    result_schema_version=LAB_SCHEMA,
+    result_schema_version=LEGACY_LAB_SCHEMA,
+)
+_NATIVE_DEFINITION: Final = LaboratoryEvidenceDefinition(
+    work_id="m48t-risk-quality-temporal",
+    runtime_relative_root=PurePosixPath("m48t-risk-quality/native-lab-results"),
+    result_id_prefix="m48q-native-risk-quality-lab",
+    document_name="manifest.json",
+    result_schema_version=NATIVE_LAB_SCHEMA,
 )
 
 
 def build_m48t_risk_quality_lab_router(
-    *, root_provider: RootProvider = lambda: None
+    *,
+    root_provider: RootProvider = lambda: None,
+    native_root_provider: RootProvider = lambda: None,
 ) -> APIRouter:
     router = APIRouter(
         prefix="/api/v1/laboratory/m48t/risk-quality",
@@ -50,15 +81,23 @@ def build_m48t_risk_quality_lab_router(
 
     @router.get("/results")
     def list_results(limit: int = Query(default=1, ge=1, le=10)) -> dict[str, object]:
-        root = _configured_root(root_provider)
-        if root is None:
-            return _empty_catalog(False)
-        candidates = _candidates(root)
+        configured = False
+        candidates: list[tuple[Path, Variant]] = []
+        providers: tuple[tuple[RootProvider, Variant, re.Pattern[str]], ...] = (
+            (root_provider, "legacy", LEGACY_RESULT_ID),
+            (native_root_provider, "native", NATIVE_RESULT_ID),
+        )
+        for provider, variant, pattern in providers:
+            root = _configured_root(provider)
+            if root is None:
+                continue
+            configured = True
+            candidates.extend((item, variant) for item in _candidates(root, pattern))
         items: list[dict[str, object]] = []
         invalid_total = 0
-        for candidate in candidates:
+        for candidate, variant in candidates:
             try:
-                items.append(_project_result(candidate))
+                items.append(_project_result(candidate, variant))
             except RuntimeError:
                 invalid_total += 1
         items.sort(
@@ -67,7 +106,7 @@ def build_m48t_risk_quality_lab_router(
         )
         return {
             "schema_version": CATALOG_VIEW_SCHEMA,
-            "configured": True,
+            "configured": configured,
             "items": items[:limit],
             "candidate_total": len(candidates),
             "invalid_total": invalid_total,
@@ -77,18 +116,37 @@ def build_m48t_risk_quality_lab_router(
     @router.get("/results/{result_id}")
     def get_result(result_id: str) -> dict[str, object]:
         try:
-            return _project_result(_resolve_candidate(root_provider, result_id))
+            candidate, variant = _resolve_candidate(
+                root_provider,
+                native_root_provider,
+                result_id,
+            )
+            return _project_result(candidate, variant)
         except RuntimeError:
-            raise HTTPException(status_code=404, detail="M4.8T result not found") from None
+            raise HTTPException(
+                status_code=404,
+                detail="M4.8T/M4.8Q result not found",
+            ) from None
 
     @router.get("/results/{result_id}/review/{case_id}.jpg")
     def get_review_image(result_id: str, case_id: str) -> FileResponse:
-        if CASE_ID.fullmatch(case_id) is None:
-            raise HTTPException(status_code=404, detail="M4.8T review case not found")
         try:
-            loaded = _load_result(_resolve_candidate(root_provider, result_id))
+            candidate, variant = _resolve_candidate(
+                root_provider,
+                native_root_provider,
+                result_id,
+            )
+            invalid_case = (variant == "legacy" and LEGACY_CASE_ID.fullmatch(case_id) is None) or (
+                variant == "native" and NATIVE_CASE_ID.fullmatch(case_id) is None
+            )
+            if invalid_case:
+                raise RuntimeError("case identity is invalid")
+            loaded = _load_result(candidate, variant)
         except RuntimeError:
-            raise HTTPException(status_code=404, detail="M4.8T result not found") from None
+            raise HTTPException(
+                status_code=404,
+                detail="M4.8T/M4.8Q review case not found",
+            ) from None
         descriptor = next(
             (
                 item
@@ -98,8 +156,10 @@ def build_m48t_risk_quality_lab_router(
             None,
         )
         if not isinstance(descriptor, dict):
-            raise HTTPException(status_code=404, detail="M4.8T review case not found")
-        candidate = loaded["root"]
+            raise HTTPException(
+                status_code=404,
+                detail="M4.8T/M4.8Q review case not found",
+            )
         path = (candidate / str(descriptor["path"])).resolve()
         if (
             not path.is_relative_to(candidate)
@@ -108,7 +168,10 @@ def build_m48t_risk_quality_lab_router(
             or descriptor.get("byte_length") != path.stat().st_size
             or descriptor.get("sha256") != _sha256(path)
         ):
-            raise HTTPException(status_code=404, detail="M4.8T review case not found")
+            raise HTTPException(
+                status_code=404,
+                detail="M4.8T/M4.8Q review case not found",
+            )
         return FileResponse(
             path,
             media_type="image/jpeg",
@@ -122,8 +185,12 @@ def build_m48t_risk_quality_lab_router(
     return router
 
 
-def _project_result(candidate: Path) -> dict[str, object]:
-    loaded = _load_result(candidate)
+def _project_result(candidate: Path, variant: Variant) -> dict[str, object]:
+    loaded = _load_result(candidate, variant)
+    return _project_native(loaded) if variant == "native" else _project_legacy(loaded)
+
+
+def _project_legacy(loaded: dict[str, Any]) -> dict[str, object]:
     manifest = loaded["manifest"]
     report = loaded["report"]
     catalog = loaded["catalog"]
@@ -143,7 +210,8 @@ def _project_result(candidate: Path) -> dict[str, object]:
         for item in catalog["cases"]
     ]
     return {
-        "schema_version": VIEW_SCHEMA,
+        "schema_version": LEGACY_VIEW_SCHEMA,
+        "variant": "legacy-coco-quality",
         "result_id": result_id,
         "created_at_utc": manifest["created_at_utc"],
         "status": manifest["status"],
@@ -165,26 +233,97 @@ def _project_result(candidate: Path) -> dict[str, object]:
     }
 
 
-def _load_result(candidate: Path) -> dict[str, Any]:
+def _project_native(loaded: dict[str, Any]) -> dict[str, object]:
+    manifest = loaded["manifest"]
+    report = loaded["report"]
+    catalog = loaded["catalog"]
+    result_id = str(manifest["result_id"])
+    review_cases = [
+        {
+            "case_id": item["case_id"],
+            "sequence": item["sequence"],
+            "frame_id": item["frame_id"],
+            "evidence_time_ns": item["evidence_time_ns"],
+            "image_url": (
+                f"/api/v1/laboratory/m48t/risk-quality/results/{result_id}"
+                f"/review/{item['case_id']}.jpg"
+            ),
+            "media_type": item["media_type"],
+            "width": item["width"],
+            "height": item["height"],
+            "byte_length": item["byte_length"],
+            "sha256": item["sha256"],
+            "geometric_resampling": item["geometric_resampling"],
+            "selection_buckets": copy.deepcopy(item["selection_buckets"]),
+            "comparison": copy.deepcopy(item["comparison"]),
+            "proposals": copy.deepcopy(item["proposals"]),
+        }
+        for item in catalog["cases"]
+    ]
+    return {
+        "schema_version": NATIVE_VIEW_SCHEMA,
+        "variant": "native-risk-review",
+        "result_id": result_id,
+        "created_at_utc": manifest["created_at_utc"],
+        "status": manifest["status"],
+        "source": copy.deepcopy(report["source"]),
+        "configuration": copy.deepcopy(report["configuration"]),
+        "method": copy.deepcopy(report["method"]),
+        "execution": copy.deepcopy(report["execution"]),
+        "metrics": copy.deepcopy(report["metrics"]),
+        "acceptance": copy.deepcopy(report["acceptance"]),
+        "decision": copy.deepcopy(report["decision"]),
+        "limitations": copy.deepcopy(report["limitations"]),
+        "review": {
+            "source_raster": copy.deepcopy(catalog["source_raster"]),
+            "overlay": copy.deepcopy(catalog["overlay"]),
+            "cases": review_cases,
+        },
+        "ground_truth": False,
+        "authority": copy.deepcopy(report["authority"]),
+        "access": "read-only",
+    }
+
+
+def _load_result(candidate: Path, variant: Variant) -> dict[str, Any]:
+    pattern = NATIVE_RESULT_ID if variant == "native" else LEGACY_RESULT_ID
+    definition = _NATIVE_DEFINITION if variant == "native" else _LEGACY_DEFINITION
     if (
         not candidate.is_dir()
         or candidate.is_symlink()
-        or RESULT_ID.fullmatch(candidate.name) is None
+        or pattern.fullmatch(candidate.name) is None
     ):
-        raise RuntimeError("M4.8T result candidate is invalid")
+        raise RuntimeError("M4.8 result candidate is invalid")
     try:
-        verify_laboratory_evidence_result(_DEFINITION, candidate)
+        verify_laboratory_evidence_result(definition, candidate)
         manifest = _read_object(candidate / "manifest.json")
         report = _read_object(candidate / "report.json")
         catalog = _read_object(candidate / "catalog.json")
     except (LaboratoryEvidenceReportError, OSError, ValueError) as exc:
-        raise RuntimeError("M4.8T result integrity failed") from exc
+        raise RuntimeError("M4.8 result integrity failed") from exc
+    if variant == "native":
+        _validate_native(candidate, manifest, report, catalog)
+    else:
+        _validate_legacy(candidate, manifest, report, catalog)
+    return {
+        "root": candidate,
+        "manifest": manifest,
+        "report": report,
+        "catalog": catalog,
+    }
+
+
+def _validate_legacy(
+    candidate: Path,
+    manifest: dict[str, Any],
+    report: dict[str, Any],
+    catalog: dict[str, Any],
+) -> None:
     identity = manifest.get("identity")
     if (
-        manifest.get("schema_version") != LAB_SCHEMA
+        manifest.get("schema_version") != LEGACY_LAB_SCHEMA
         or manifest.get("result_id") != candidate.name
-        or manifest.get("status")
-        != "complete-quality-gate-failed-temporal-invariant-passed"
+        or manifest.get("status") != "complete-quality-gate-failed-temporal-invariant-passed"
         or manifest.get("completed") is not True
         or manifest.get("bounded_question_accepted") is not False
         or manifest.get("ground_truth") is not False
@@ -194,47 +333,143 @@ def _load_result(candidate: Path) -> dict[str, Any]:
         or not candidate.name.endswith(str(manifest.get("identity_sha256")))
         or identity.get("authority") != false_authority()
         or manifest.get("authority") != false_authority()
-        or report.get("schema_version") != REPORT_SCHEMA
+        or report.get("schema_version") != LEGACY_REPORT_SCHEMA
         or report.get("result_id") != candidate.name
         or report.get("authority") != false_authority()
         or report.get("decision", {}).get("quality_accepted") is not False
         or report.get("decision", {}).get("temporal_invariant_passed") is not True
-        or catalog.get("schema_version") != CATALOG_SCHEMA
+        or catalog.get("schema_version") != LEGACY_CATALOG_SCHEMA
         or catalog.get("result_id") != candidate.name
         or catalog.get("case_count") != 16
         or not isinstance(catalog.get("cases"), list)
         or len(catalog["cases"]) != 16
-        or any(not _valid_case(item) for item in catalog["cases"])
+        or any(not _valid_legacy_case(item) for item in catalog["cases"])
     ):
         raise RuntimeError("M4.8T result contract changed")
-    return {"root": candidate, "manifest": manifest, "report": report, "catalog": catalog}
 
 
-def _valid_case(value: object) -> bool:
+def _validate_native(
+    candidate: Path,
+    manifest: dict[str, Any],
+    report: dict[str, Any],
+    catalog: dict[str, Any],
+) -> None:
+    identity = manifest.get("identity")
+    cases = catalog.get("cases")
+    if (
+        manifest.get("schema_version") != NATIVE_LAB_SCHEMA
+        or manifest.get("result_id") != candidate.name
+        or manifest.get("status") != "complete-review-ready-quality-not-adjudicated"
+        or manifest.get("completed") is not True
+        or manifest.get("bounded_question_accepted") is not True
+        or manifest.get("ground_truth") is not False
+        or not isinstance(manifest.get("created_at_utc"), str)
+        or not isinstance(identity, dict)
+        or manifest.get("identity_sha256") != _canonical_sha256(identity)
+        or not candidate.name.endswith(str(manifest.get("identity_sha256")))
+        or identity.get("authority") != false_authority()
+        or manifest.get("authority") != false_authority()
+        or report.get("schema_version") != NATIVE_REPORT_SCHEMA
+        or report.get("result_id") != candidate.name
+        or report.get("authority") != false_authority()
+        or report.get("decision", {}).get("review_ready") is not True
+        or report.get("decision", {}).get("quality_evaluated") is not False
+        or report.get("decision", {}).get("candidate_accepted") is not False
+        or catalog.get("schema_version") != NATIVE_CATALOG_SCHEMA
+        or catalog.get("result_id") != candidate.name
+        or catalog.get("case_count") != 24
+        or catalog.get("ground_truth") is not False
+        or not isinstance(cases, list)
+        or len(cases) != 24
+        or any(not _valid_native_case(item) for item in cases)
+    ):
+        raise RuntimeError("M4.8Q result contract changed")
+
+
+def _valid_legacy_case(value: object) -> bool:
     return (
         isinstance(value, dict)
         and isinstance(value.get("case_id"), str)
-        and CASE_ID.fullmatch(value["case_id"]) is not None
+        and LEGACY_CASE_ID.fullmatch(value["case_id"]) is not None
         and value.get("image_id") == int(value["case_id"])
         and value.get("path") == f"review/review-{value['case_id']}.jpg"
         and value.get("media_type") == "image/jpeg"
-        and isinstance(value.get("byte_length"), int)
+        and _valid_file_proof(value)
+    )
+
+
+def _valid_native_case(value: object) -> bool:
+    if not isinstance(value, dict) or not isinstance(value.get("case_id"), str):
+        return False
+    case_id = value["case_id"]
+    proposals = value.get("proposals")
+    return (
+        NATIVE_CASE_ID.fullmatch(case_id) is not None
+        and value.get("sequence") == int(case_id)
+        and value.get("frame_id") == f"frame-{case_id}"
+        and isinstance(value.get("evidence_time_ns"), int)
+        and value.get("path") == f"cases/frame-{case_id}.jpg"
+        and value.get("media_type") == "image/jpeg"
+        and value.get("width") == 800
+        and value.get("height") == 600
+        and value.get("geometric_resampling") is False
+        and isinstance(value.get("selection_buckets"), list)
+        and isinstance(value.get("comparison"), dict)
+        and isinstance(proposals, list)
+        and len(proposals) > 0
+        and all(_valid_native_proposal(item) for item in proposals)
+        and _valid_file_proof(value)
+    )
+
+
+def _valid_native_proposal(value: object) -> bool:
+    if not isinstance(value, dict):
+        return False
+    box = value.get("box_xyxy")
+    return (
+        isinstance(value.get("proposal_id"), str)
+        and isinstance(value.get("class_name"), str)
+        and isinstance(value.get("risk_family"), str)
+        and isinstance(value.get("score"), (int, float))
+        and not isinstance(value.get("score"), bool)
+        and 0.25 <= value["score"] <= 1
+        and isinstance(box, list)
+        and len(box) == 4
+        and all(isinstance(item, (int, float)) and not isinstance(item, bool) for item in box)
+        and 0 <= box[0] < box[2] <= 800
+        and 0 <= box[1] < box[3] <= 600
+    )
+
+
+def _valid_file_proof(value: dict[str, Any]) -> bool:
+    return (
+        isinstance(value.get("byte_length"), int)
         and value["byte_length"] > 0
         and isinstance(value.get("sha256"), str)
         and re.fullmatch(r"[a-f0-9]{64}", value["sha256"]) is not None
     )
 
 
-def _resolve_candidate(provider: RootProvider, result_id: str) -> Path:
-    if RESULT_ID.fullmatch(result_id) is None:
-        raise HTTPException(status_code=404, detail="M4.8T result not found")
+def _resolve_candidate(
+    legacy_provider: RootProvider,
+    native_provider: RootProvider,
+    result_id: str,
+) -> tuple[Path, Variant]:
+    provider: RootProvider
+    variant: Variant
+    if NATIVE_RESULT_ID.fullmatch(result_id) is not None:
+        provider, variant = native_provider, "native"
+    elif LEGACY_RESULT_ID.fullmatch(result_id) is not None:
+        provider, variant = legacy_provider, "legacy"
+    else:
+        raise HTTPException(status_code=404, detail="M4.8 result not found")
     root = _configured_root(provider)
     if root is None:
-        raise HTTPException(status_code=404, detail="M4.8T result not found")
+        raise HTTPException(status_code=404, detail="M4.8 result not found")
     candidate = (root / result_id).resolve()
     if candidate.parent != root or candidate.is_symlink() or not candidate.is_dir():
-        raise HTTPException(status_code=404, detail="M4.8T result not found")
-    return candidate
+        raise HTTPException(status_code=404, detail="M4.8 result not found")
+    return candidate, variant
 
 
 def _configured_root(provider: RootProvider) -> Path | None:
@@ -251,29 +486,18 @@ def _configured_root(provider: RootProvider) -> Path | None:
     return root if root.is_dir() else None
 
 
-def _candidates(root: Path) -> list[Path]:
+def _candidates(root: Path, pattern: re.Pattern[str]) -> list[Path]:
     return sorted(
         (
             item
             for item in root.iterdir()
-            if item.is_dir() and not item.is_symlink() and RESULT_ID.fullmatch(item.name)
+            if item.is_dir() and not item.is_symlink() and pattern.fullmatch(item.name)
         ),
         key=lambda item: item.stat().st_mtime_ns,
         reverse=True,
     )
 
 
-def _empty_catalog(configured: bool) -> dict[str, object]:
-    return {
-        "schema_version": CATALOG_VIEW_SCHEMA,
-        "configured": configured,
-        "items": [],
-        "candidate_total": 0,
-        "invalid_total": 0,
-        "access": "read-only",
-    }
-
-
 def _read_object(path: Path) -> dict[str, Any]:
     value = json.loads(path.read_text("utf-8"))
     if not isinstance(value, dict):

tests/test_geometry_association_provider.py

@@ -152,6 +152,15 @@ def test_profile_is_strict_digest_bound_and_store_accepts_exact_evidence() -> No
     assert store.profile.local_surface_sha256 == (
         "f57eb2485b6cef47f2a97a2d9ff1aa9fd9265fe1eb69cd5852d12f39e13b8bc6"
     )
+    step_candidates = store.point_step_candidates_for_frame(0)
+    assert step_candidates is not None
+    assert step_candidates.shape == (2389,)
+    assert step_candidates.dtype == np.uint8
+    assert step_candidates.flags.writeable is False
+    with pytest.raises(ValueError):
+        step_candidates[0] = 0
+    with pytest.raises(GeometryProviderError, match="frame index"):
+        store.point_step_candidates_for_frame(True)
 
 
 def test_provider_arbitrates_points_and_publishes_classless_geometry_only() -> None:

tests/test_laboratory_evidence_registry.py

@@ -127,7 +127,7 @@ def test_product_registry_declares_every_advanced_evidence_source() -> None:
         repository_root / "config" / "laboratories"
     )
 
-    assert len(registry.definitions) == 38
+    assert len(registry.definitions) == 39
     assert {item.work_id for item in registry.definitions} >= {
         "e31-source-binding",
         "e46j-raw-fisheye-realtime",
@@ -141,15 +141,26 @@ def test_product_registry_declares_every_advanced_evidence_source() -> None:
         "m47-reference-graph-shadow",
         "m48-object-centric-quality",
         "m48-small-static-passage-regression",
+        "m48-static-occupancy-qualification",
         "m48s-fixed-class-detector",
         "m48t-risk-quality-temporal",
     }
     m48 = next(
-        item for item in registry.definitions
-        if item.work_id == "m48-object-centric-quality"
+        item for item in registry.definitions if item.work_id == "m48-object-centric-quality"
     )
     assert [variant.phase for variant in m48.evidence_variants] == ["review", "result"]
     assert [variant.result_id_prefix for variant in m48.evidence_variants] == [
         "m48-object-quality-pack",
         "m48-object-quality-result",
     ]
+    m48t = next(
+        item for item in registry.definitions if item.work_id == "m48t-risk-quality-temporal"
+    )
+    assert [variant.phase for variant in m48t.evidence_variants] == [
+        "legacy-quality",
+        "result",
+    ]
+    assert [variant.result_id_prefix for variant in m48t.evidence_variants] == [
+        "m48t-risk-quality-temporal-lab",
+        "m48q-native-risk-quality-lab",
+    ]

tests/test_laboratory_execution.py

@@ -92,6 +92,7 @@ def test_repository_registry_classifies_every_evidence_definition() -> None:
 
     assert {row.work_id for row in execution.definitions} == {
         "m48-small-static-passage-regression",
+        "m48-static-occupancy-qualification",
         "m48-object-centric-quality",
         "m4-replay-threat",
         "e33-worker-shadow",
@@ -108,6 +109,9 @@ def test_repository_registry_classifies_every_evidence_definition() -> None:
     assert by_work_id["m48-object-centric-quality"].evidence_contract == (
         "missioncore.m48-object-centric-quality-result/v1"
     )
+    assert by_work_id["m48-static-occupancy-qualification"].evidence_contract == (
+        "missioncore.m48-static-occupancy-qualification-result/v1"
+    )
     assert by_work_id["e47-semantic-slam-shadow"].lifecycle == "experimental"
     assert by_work_id["e47-semantic-slam-shadow"].isolation == "bounded-adapter"
     assert by_work_id["m48s-fixed-class-detector"].lifecycle == "experimental"

tests/test_laboratory_value_review_registry.py

@@ -80,7 +80,7 @@ def test_product_value_review_registry_covers_reviewed_laboratory_families() ->
         root / "config" / "laboratory-value-review.json"
     )
 
-    assert len(registry.entries) == 37
+    assert len(registry.entries) == 38
     assert {entry.catalog_id for entry in registry.entries} >= {
         "e28-local-surface",
         "e46d-temporal-failure-audit",
@@ -88,6 +88,7 @@ def test_product_value_review_registry_covers_reviewed_laboratory_families() ->
         "l31-pointpillars-ravnoves",
         "l34f-adjudicated-reference",
         "m4-replay-threat",
+        "m48-static-occupancy-qualification",
         "m48s-fixed-class-detector",
         "m48t-risk-quality-temporal",
     }

tests/test_m48_object_quality_api.py

@@ -217,6 +217,82 @@ def _fixture(
         lambda _: regression_result,
     )
 
+    static_occupancy_result_id = f"m48-static-occupancy-qualification-{'e' * 64}"
+    static_occupancy_root = tmp_path / "static-occupancy" / static_occupancy_result_id
+    static_occupancy_root.mkdir(parents=True)
+    static_occupancy_result = SimpleNamespace(
+        result_id=static_occupancy_result_id,
+        result_root=static_occupancy_root,
+        manifest={
+            "created_at_utc": "2026-08-26T12:00:00Z",
+            "accepted": False,
+        },
+        report={
+            "source": {
+                "m47_lab_result_id": f"m47-reference-graph-lab-{'c' * 64}",
+                "small_static_result_id": regression_result_id,
+            },
+            "configuration": {
+                "run_label": "M4.8R2",
+                "pipeline_id": "m4-current-rolling-plus-step-static-occupancy/v1",
+                "experiment_id": "m48-static-occupancy-qualification/v1",
+            },
+            "metrics": {
+                "operator_static_anchor_count": 1,
+                "baseline_qualified_count": 0,
+                "candidate_qualified_count": 1,
+                "unresolved_unknown_count": 0,
+                "critical_near_anchor_count": 1,
+                "critical_near_baseline_recall": 0.0,
+                "critical_near_candidate_recall": 1.0,
+                "approach_anchor_count": 0,
+                "approach_baseline_recall": 0.0,
+                "approach_candidate_recall": 0.0,
+                "canonical_engineering_anchor_count": 4,
+                "canonical_engineering_recall": 1.0,
+                "false_free_count": 0,
+            },
+            "gates": {
+                "critical_near_candidate_recall": True,
+                "approach_candidate_recall": False,
+                "canonical_engineering_recall": True,
+                "zero_false_free": True,
+                "independent_truth_available": False,
+            },
+            "decision": {
+                "state": "partial-static-occupancy-qualification",
+                "critical_near_candidate_ready_for_shadow": True,
+                "production_accepted": False,
+                "summary": "fixture",
+                "next_action": "worker shadow",
+            },
+        },
+        cases=(
+            {
+                "anchor_id": regression_anchor_id,
+                "clip_id": "neutral-clip-01",
+                "sequence": 1,
+                "extent_xyxy": [0.2, 0.2, 0.3, 0.4],
+                "distance_m": 3.0,
+                "distance_band": "critical-near",
+                "accepted_graph": {
+                    "matched": False,
+                    "component_count": 0,
+                    "components": [],
+                    "free_space_claimed": False,
+                },
+                "baseline_qualified": False,
+                "candidate_qualified": True,
+                "outcome": "candidate-qualified",
+            },
+        ),
+    )
+    monkeypatch.setattr(
+        api,
+        "read_m48_static_occupancy_qualification",
+        lambda _: static_occupancy_result,
+    )
+
     observations: dict[str, list[dict[str, Any]]] = {
         "reviews": [],
         "adjudications": [],
@@ -444,6 +520,7 @@ def _fixture(
             truth_root_provider=lambda: tmp_path / "truth",
             result_root_provider=lambda: tmp_path / "results",
             small_static_result_root_provider=lambda: tmp_path / "small-static",
+            static_occupancy_result_root_provider=lambda: tmp_path / "static-occupancy",
             camera_frame_provider=camera,
             camera_playback_provider=camera_playback,  # type: ignore[arg-type]
             spatial_evidence_provider=spatial_frame if spatial else None,
@@ -1128,3 +1205,31 @@ def test_m48_small_static_regression_is_separate_read_only_assisted_evidence(
     assert body["ground_truth"] is False
     assert body["camera_url"].endswith("/frames/1/camera")
     assert body["spatial_url"].endswith("/frames/1/spatial")
+
+
+def test_m48_static_occupancy_qualification_is_read_only_bounded_evidence(
+    tmp_path: Path,
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    client, _, _ = _fixture(tmp_path, monkeypatch, spatial=True)
+    result_id = f"m48-static-occupancy-qualification-{'e' * 64}"
+
+    summary = client.get(
+        f"/api/v1/laboratory/m48/regressions/static-occupancy/{result_id}"
+    )
+    assert summary.status_code == 200
+    assert summary.headers["cache-control"] == "no-store"
+    assert summary.json()["run_label"] == "M4.8R2"
+    assert summary.json()["accepted"] is False
+    assert summary.json()["ground_truth"] is False
+    assert summary.json()["independent_truth"] is False
+    assert summary.json()["metrics"]["critical_near_candidate_recall"] == 1.0
+    assert summary.json()["decision"]["production_accepted"] is False
+
+    catalog = client.get(
+        f"/api/v1/laboratory/m48/regressions/static-occupancy/{result_id}/cases"
+    )
+    assert catalog.status_code == 200
+    assert catalog.json()["case_count"] == 1
+    assert catalog.json()["cases"][0]["outcome"] == "candidate-qualified"
+    assert catalog.json()["cases"][0]["accepted_graph"]["free_space_claimed"] is False

tests/test_m48_static_occupancy_qualification.py

@@ -0,0 +1,106 @@
+from __future__ import annotations
+
+from pathlib import Path
+
+import pytest
+
+import k1link.laboratory.m48_static_occupancy_qualification as qualification
+from k1link.laboratory.evidence_registry import LaboratoryEvidenceRegistry
+from k1link.laboratory.evidence_report import verify_laboratory_evidence_result
+
+REPOSITORY_ROOT = Path(__file__).resolve().parents[1]
+AUTHORITY = {
+    "mode": "replay-simulated",
+    "physical_live": False,
+    "commands_enabled": False,
+    "actuation_allowed": False,
+    "navigation_or_safety_accepted": False,
+}
+
+
+def _sealed_result(tmp_path: Path) -> qualification.M48StaticOccupancyQualificationResult:
+    identity = {
+        "schema_version": qualification.M48_STATIC_OCCUPANCY_RESULT_SCHEMA,
+        "human_lab_id": "M4.8R2",
+        "run_label": "fixture",
+        "run_created_at_utc": "2026-08-26T12:00:00Z",
+        "authority": AUTHORITY,
+    }
+    result_id = qualification.M48_STATIC_OCCUPANCY_PREFIX + qualification._canonical_sha256(
+        identity
+    )
+    report = {
+        "schema_version": qualification.M48_STATIC_OCCUPANCY_REPORT_SCHEMA,
+        "result_id": result_id,
+        "metrics": {
+            "operator_static_anchor_count": 1,
+            "candidate_qualified_count": 1,
+        },
+        "decision": {"production_accepted": False},
+        "authority": AUTHORITY,
+    }
+    cases = (
+        {
+            "schema_version": qualification.M48_STATIC_OCCUPANCY_CASE_SCHEMA,
+            "anchor_id": "anchor-" + "a" * 24,
+            "sequence": 10,
+            "baseline_qualified": False,
+            "candidate_qualified": True,
+            "outcome": "candidate-qualified",
+        },
+    )
+    canonical = (
+        {
+            "schema_version": qualification.M48_STATIC_OCCUPANCY_CANONICAL_SCHEMA,
+            "anchor_id": "hemisphere-01",
+            "sequence": 1880,
+            "matched": True,
+        },
+    )
+    destination = tmp_path / "results" / result_id
+    qualification._publish_result(
+        destination,
+        identity,
+        "2026-08-26T12:00:00Z",
+        False,
+        report,
+        cases,
+        canonical,
+    )
+    return qualification.read_m48_static_occupancy_qualification(destination)
+
+
+def test_seals_bounded_static_occupancy_evidence_without_production_authority(
+    tmp_path: Path,
+) -> None:
+    result = _sealed_result(tmp_path)
+
+    assert result.manifest["accepted"] is False
+    assert result.manifest["ground_truth"] is False
+    assert result.manifest["authority"] == AUTHORITY
+    assert result.report["decision"]["production_accepted"] is False
+    assert result.cases[0]["outcome"] == "candidate-qualified"
+
+    registry = LaboratoryEvidenceRegistry.from_directory(
+        REPOSITORY_ROOT / "config/laboratories"
+    )
+    definition = next(
+        row
+        for row in registry.definitions
+        if row.work_id == "m48-static-occupancy-qualification"
+    )
+    proof = verify_laboratory_evidence_result(definition, result.result_root)
+    assert proof["result_id"] == result.result_id
+    assert proof["artifact_count"] == 3
+
+
+def test_reader_rejects_changed_static_occupancy_case_ledger(tmp_path: Path) -> None:
+    result = _sealed_result(tmp_path)
+    cases_path = result.result_root / "cases.jsonl"
+    cases_path.write_bytes(cases_path.read_bytes() + b"{}\n")
+
+    with pytest.raises(
+        qualification.M48StaticOccupancyQualificationError,
+        match="artifact proof",
+    ):
+        qualification.read_m48_static_occupancy_qualification(result.result_root)

tests/test_m48q_native_risk_case_mining.py

@@ -0,0 +1,90 @@
+from __future__ import annotations
+
+import importlib.util
+import sys
+from pathlib import Path
+
+import pytest
+
+REPOSITORY_ROOT = Path(__file__).resolve().parents[1]
+RUNNER_PATH = (
+    REPOSITORY_ROOT / "experiments" / "perception" / "run_m48q_native_risk_case_mining_worker.py"
+)
+SPEC = importlib.util.spec_from_file_location("m48q_case_mining", RUNNER_PATH)
+assert SPEC is not None and SPEC.loader is not None
+MODULE = importlib.util.module_from_spec(SPEC)
+sys.modules[SPEC.name] = MODULE
+SPEC.loader.exec_module(MODULE)
+
+
+def candidate(sequence: int, *buckets: str):
+    return MODULE.FrameCandidate(
+        sequence=sequence,
+        frame_id=f"frame-{sequence:06d}",
+        evidence_time_ns=sequence * 1_000_000,
+        proposals=(),
+        native_count=0,
+        legacy_count=0,
+        matched_count=0,
+        buckets=frozenset(buckets),
+    )
+
+
+def test_selection_is_deterministic_balanced_and_separated() -> None:
+    candidates = [
+        candidate(sequence, "person" if sequence % 2 == 0 else "vehicle")
+        for sequence in range(0, 400, 5)
+    ]
+    quotas = {"person": 3, "vehicle": 3}
+
+    first = MODULE.select_cases(
+        candidates,
+        bucket_quotas=quotas,
+        minimum_sequence_separation=10,
+    )
+    second = MODULE.select_cases(
+        candidates,
+        bucket_quotas=quotas,
+        minimum_sequence_separation=10,
+    )
+
+    assert [item.sequence for item in first] == [item.sequence for item in second]
+    assert len(first) == 6
+    assert all(
+        abs(left.sequence - right.sequence) >= 10
+        for index, left in enumerate(first)
+        for right in first[index + 1 :]
+    )
+
+
+def test_selection_refuses_missing_bucket_coverage() -> None:
+    with pytest.raises(MODULE.M48QCaseMiningError, match="animal produced 0/1"):
+        MODULE.select_cases(
+            [candidate(0, "person")],
+            bucket_quotas={"animal": 1},
+            minimum_sequence_separation=1,
+        )
+
+
+def test_profile_freezes_raw_raster_and_false_authority() -> None:
+    import json
+
+    profile = json.loads(
+        (
+            REPOSITORY_ROOT / "config" / "perception" / "m48q-native-risk-case-mining-v1.json"
+        ).read_text("utf-8")
+    )
+
+    assert profile["source"] == {
+        "source_id": "RAVNOVES00",
+        "frame_count": 4489,
+        "raster_width": 800,
+        "raster_height": 600,
+        "video_sha256": "cadd1696ff000904eb78633a0a8418104b8024f178b91f3421789021ccb160e8",
+        "geometric_resampling": False,
+        "rectification": False,
+        "warp": False,
+    }
+    assert sum(profile["selection"]["bucket_quotas"].values()) == 24
+    assert profile["scope"]["quality_evaluated"] is False
+    assert profile["authority"] == MODULE.FALSE_AUTHORITY

tests/test_m48t_risk_quality_lab_api.py

@@ -6,6 +6,18 @@ from pathlib import Path
 from fastapi import FastAPI
 from fastapi.testclient import TestClient
 
+from k1link.laboratory.m48q_native_risk_quality_lab import (
+    CATALOG_SCHEMA as NATIVE_CATALOG_SCHEMA,
+)
+from k1link.laboratory.m48q_native_risk_quality_lab import (
+    LAB_SCHEMA as NATIVE_LAB_SCHEMA,
+)
+from k1link.laboratory.m48q_native_risk_quality_lab import (
+    REPORT_SCHEMA as NATIVE_REPORT_SCHEMA,
+)
+from k1link.laboratory.m48q_native_risk_quality_lab import (
+    RESULT_PREFIX as NATIVE_RESULT_PREFIX,
+)
 from k1link.laboratory.m48t_risk_quality_lab import (
     CATALOG_SCHEMA,
     LAB_SCHEMA,
@@ -150,3 +162,129 @@ def test_m48t_lab_api_fails_closed_after_visual_tamper(tmp_path: Path) -> None:
     catalog = client.get("/api/v1/laboratory/m48t/risk-quality/results")
     assert catalog.json()["items"] == []
     assert catalog.json()["invalid_total"] == 1
+
+
+def _native_fixture(tmp_path: Path) -> tuple[TestClient, Path, str]:
+    root = tmp_path / "native-results"
+    root.mkdir()
+    identity = {"schema_version": NATIVE_LAB_SCHEMA, "authority": false_authority()}
+    identity_sha256 = hashlib.sha256(canonical_json(identity)).hexdigest()
+    result_id = NATIVE_RESULT_PREFIX + identity_sha256
+    result_root = root / result_id
+    cases_root = result_root / "cases"
+    cases_root.mkdir(parents=True)
+    cases = []
+    image_paths = []
+    for index in range(24):
+        case_id = f"{index * 20 + 12:06d}"
+        image_path = cases_root / f"frame-{case_id}.jpg"
+        image_path.write_bytes(b"native-jpeg" + bytes([index]))
+        image_paths.append(image_path)
+        cases.append(
+            {
+                "case_id": case_id,
+                "sequence": int(case_id),
+                "frame_id": f"frame-{case_id}",
+                "evidence_time_ns": 35_000_000_000 + index * 1_000_000,
+                "path": f"cases/{image_path.name}",
+                "media_type": "image/jpeg",
+                "width": 800,
+                "height": 600,
+                "byte_length": image_path.stat().st_size,
+                "sha256": hashlib.sha256(image_path.read_bytes()).hexdigest(),
+                "geometric_resampling": False,
+                "selection_buckets": ["person"],
+                "comparison": {
+                    "native_detection_count": 1,
+                    "legacy_704_detection_count": 1,
+                    "matched_detection_count_iou_at_least_0_5": 1,
+                },
+                "proposals": [
+                    {
+                        "proposal_id": f"proposal-{index}-0",
+                        "class_name": "person",
+                        "risk_family": "person",
+                        "score": 0.75,
+                        "box_xyxy": [10.0, 20.0, 100.0, 200.0],
+                    }
+                ],
+            }
+        )
+    catalog = {
+        "schema_version": NATIVE_CATALOG_SCHEMA,
+        "result_id": result_id,
+        "case_count": 24,
+        "source_raster": {"width": 800, "height": 600},
+        "overlay": {"client_rendered": True, "toggleable": True},
+        "ground_truth": False,
+        "cases": cases,
+    }
+    report = {
+        "schema_version": NATIVE_REPORT_SCHEMA,
+        "result_id": result_id,
+        "source": {},
+        "configuration": {},
+        "method": {},
+        "execution": {},
+        "metrics": {},
+        "acceptance": {},
+        "decision": {
+            "review_ready": True,
+            "quality_evaluated": False,
+            "candidate_accepted": False,
+        },
+        "limitations": [],
+        "authority": false_authority(),
+    }
+    catalog_path = result_root / "catalog.json"
+    report_path = result_root / "report.json"
+    _write_json(catalog_path, catalog)
+    _write_json(report_path, report)
+    artifacts = [
+        _descriptor(catalog_path, result_root, "visual-evidence-catalog", "application/json"),
+        _descriptor(report_path, result_root, "laboratory-report", "application/json"),
+        *[
+            _descriptor(path, result_root, "visual-evidence-native-raw-fisheye-frame", "image/jpeg")
+            for path in image_paths
+        ],
+    ]
+    manifest = {
+        "schema_version": NATIVE_LAB_SCHEMA,
+        "result_id": result_id,
+        "identity_sha256": identity_sha256,
+        "identity": identity,
+        "created_at_utc": "2026-08-26T09:45:15.574709Z",
+        "status": "complete-review-ready-quality-not-adjudicated",
+        "completed": True,
+        "bounded_question_accepted": True,
+        "ground_truth": False,
+        "authority": false_authority(),
+        "artifacts": artifacts,
+    }
+    _write_json(result_root / "manifest.json", manifest)
+    app = FastAPI()
+    app.include_router(build_m48t_risk_quality_lab_router(native_root_provider=lambda: root))
+    return TestClient(app), result_root, result_id
+
+
+def test_m48q_lab_api_projects_native_raw_cases_without_quality_promotion(
+    tmp_path: Path,
+) -> None:
+    client, result_root, result_id = _native_fixture(tmp_path)
+
+    catalog = client.get("/api/v1/laboratory/m48t/risk-quality/results")
+    assert catalog.status_code == 200
+    assert catalog.json()["items"][0]["variant"] == "native-risk-review"
+    result = client.get(f"/api/v1/laboratory/m48t/risk-quality/results/{result_id}")
+    assert result.status_code == 200
+    assert result.json()["ground_truth"] is False
+    assert result.json()["decision"]["quality_evaluated"] is False
+    assert len(result.json()["review"]["cases"]) == 24
+    assert result.json()["review"]["cases"][0]["geometric_resampling"] is False
+
+    case_id = "000012"
+    image = client.get(
+        f"/api/v1/laboratory/m48t/risk-quality/results/{result_id}/review/{case_id}.jpg"
+    )
+    assert image.status_code == 200
+    assert image.content == (result_root / f"cases/frame-{case_id}.jpg").read_bytes()