Complete temporal detection safety gate

CHANGELOG.md

@@ -27,6 +27,21 @@
 - Made system capabilities report real PostGIS and configured local YOLO
   state, added request IDs and exception logging, reduced SQL engine logging,
   and terminalized impossible orphaned work after all-in-one restarts.
+- Added non-logging PostgreSQL credential rotation with atomic `.env` update,
+  role update, managed-container restart and health verification.
+- Completed a current secure Tower backup and isolated restore drill with
+  PostGIS, Alembic and critical table-count reconciliation.
+- Removed every implicit first-raster fallback from Detection Lab; raster
+  selection is now an explicit operator decision in normal runs, guided runs
+  and calibration.
+- Added fail-closed detection source and QA temporal compatibility checks.
+  Historical orthophotos marked unsupported cannot run through the current
+  model, and historical QA requires an overlapping reference validity period.
+- Persisted the temporal compatibility decision in existing QualityCheck
+  parameters/findings and added correlated request, job, analysis-run and
+  quality-check logging.
+- Added a read-only stale-runtime report plus an explicitly confirmed
+  reconciliation mode.
 
 ## Sprint 240 Operational forest, agriculture, nature and soil themes (2026-07-17)
 

backend/app/core/request_context.py

@@ -0,0 +1,18 @@
+from __future__ import annotations
+
+from contextvars import ContextVar, Token
+
+
+_request_id: ContextVar[str] = ContextVar("geointel_request_id", default="-")
+
+
+def get_request_id() -> str:
+    return _request_id.get()
+
+
+def set_request_id(value: str) -> Token:
+    return _request_id.set(value)
+
+
+def reset_request_id(token: Token) -> None:
+    _request_id.reset(token)

backend/app/main.py

@@ -1,6 +1,8 @@
 from __future__ import annotations
 
 import logging
+import re
+import time
 import uuid
 from contextlib import asynccontextmanager
 
@@ -13,11 +15,13 @@ from app.api.routes import analysis, areas, assistant, datasets, demo, detection
 from app.core.config import get_settings
 from app.core.errors import AppError
 from app.core.logging import configure_logging
+from app.core.request_context import reset_request_id, set_request_id
 from app.db.session import SessionLocal
 from app.services.runtime_reconciliation_service import RuntimeReconciliationService
 
 
 logger = logging.getLogger("geointel")
+SAFE_REQUEST_ID = re.compile(r"^[A-Za-z0-9._:-]{1,128}$")
 
 
 def _to_error_payload(
@@ -91,11 +95,25 @@ def create_app() -> FastAPI:
 
     @app.middleware("http")
     async def request_identity(request: Request, call_next):
-        request_id = request.headers.get("x-request-id") or str(uuid.uuid4())
+        supplied_request_id = request.headers.get("x-request-id", "")
+        request_id = supplied_request_id if SAFE_REQUEST_ID.fullmatch(supplied_request_id) else str(uuid.uuid4())
         request.state.request_id = request_id
+        token = set_request_id(request_id)
+        started_at = time.perf_counter()
+        try:
             response = await call_next(request)
             response.headers["x-request-id"] = request_id
+            logger.info(
+                "request_complete request_id=%s method=%s path=%s status=%s duration_ms=%.1f",
+                request_id,
+                request.method,
+                request.url.path,
+                response.status_code,
+                (time.perf_counter() - started_at) * 1000,
+            )
             return response
+        finally:
+            reset_request_id(token)
 
     @app.exception_handler(AppError)
     async def app_error(request: Request, exc: AppError):  # noqa: ARG001

backend/app/services/detection_service.py

@@ -2,6 +2,7 @@ from __future__ import annotations
 
 import uuid
 import json
+import logging
 from datetime import UTC, datetime
 from pathlib import Path
 from typing import Any
@@ -13,6 +14,7 @@ from sqlalchemy import func
 
 from app.core.config import Settings, get_settings
 from app.core.errors import AppError
+from app.core.request_context import get_request_id
 from app.models import AnalysisRun, Dataset, Detection, Job, Project, VectorFeature
 from app.schemas.detection import DetectionListResponse, DetectionRead, DetectionRunListResponse, DetectionRunRead, DetectionRunResponse
 from app.services.detection_georeferencing import pixel_bbox_to_epsg4326_polygon
@@ -21,9 +23,13 @@ from app.services.model_asset_catalog_service import ModelAssetCatalogService
 from app.services.model_registry_service import ModelRegistryService
 from app.services.qa_service import QaService
 from app.services.quality_service import QualityService
+from app.services.temporal_compatibility_service import TemporalCompatibilityService
 from app.services.yolo_adapter import YoloDetectionAdapter
 
 
+logger = logging.getLogger("geointel.detection")
+
+
 class DetectionService:
     @staticmethod
     def _now() -> datetime:
@@ -58,6 +64,7 @@ class DetectionService:
                 details={"dataset_type": dataset.dataset_type},
                 status_code=400,
             )
+        TemporalCompatibilityService.ensure_detection_source_supported(dataset)
 
         selected_model_asset = None
         if model_id == resolved_settings.yolo_model_id and model_asset_id:
@@ -96,6 +103,15 @@ class DetectionService:
         }
         job = DetectionService._create_job(db, project_id, dataset_id, run_parameters)
         analysis_run = DetectionService._create_analysis_run(db, project_id, dataset_id, job.id, model, run_parameters)
+        logger.info(
+            "detection_started request_id=%s project_id=%s dataset_id=%s job_id=%s analysis_run_id=%s model_id=%s",
+            get_request_id(),
+            project_id,
+            dataset_id,
+            job.id,
+            analysis_run.id,
+            model.model_id,
+        )
 
         if not model.configured:
             message = model.limitation_message
@@ -281,6 +297,13 @@ class DetectionService:
             raise AppError(code="INVALID_DATASET_SCOPE", message="Reference dataset does not belong to detection project", status_code=400)
         if reference_dataset.dataset_type not in {"vector", "geojson"}:
             raise AppError(code="INVALID_DATASET_TYPE", message="Reference dataset must be vector data", status_code=400)
+        candidate_dataset = db.get(Dataset, run.dataset_id)
+        if not candidate_dataset:
+            raise AppError(code="DATASET_NOT_FOUND", message="Detection source dataset not found", status_code=404)
+        temporal_compatibility = TemporalCompatibilityService.assess_detection_qa(
+            candidate_dataset,
+            reference_dataset,
+        )
 
         detections = DetectionService._query_detection_rows(
             db,
@@ -421,6 +444,7 @@ class DetectionService:
                 "class_name": class_name,
                 "min_confidence": min_confidence,
                 "coverage_policy": coverage_summary["mode"],
+                "temporal_compatibility": temporal_compatibility,
             },
             findings={
                 "matches": evidence.matches,
@@ -429,6 +453,7 @@ class DetectionService:
                 "warnings": coverage_warnings + evidence.warnings,
                 "unsupported_geometry": evidence.unsupported,
                 "coverage": coverage_summary,
+                "temporal_compatibility": temporal_compatibility,
                 "box_to_footprint_diagnostics": box_to_footprint_diagnostics,
                 "match_evidence": evidence.match_evidence,
                 "false_positive_evidence": evidence.false_positive_evidence,
@@ -443,6 +468,17 @@ class DetectionService:
                 "false_negative_count": evidence.false_negatives,
             },
         )
+        logger.info(
+            "detection_qa_completed request_id=%s job_id=%s analysis_run_id=%s quality_check_id=%s "
+            "candidate_dataset_id=%s reference_dataset_id=%s status=%s",
+            get_request_id(),
+            run.job_id,
+            analysis_run_id,
+            quality_check.id,
+            run.dataset_id,
+            reference_dataset_id,
+            status,
+        )
         return {
             "status": status,
             "quality_check_id": str(quality_check.id),
@@ -462,6 +498,7 @@ class DetectionService:
             "iou_threshold": iou_threshold,
             "warnings": coverage_warnings + evidence.warnings,
             "coverage": coverage_summary,
+            "temporal_compatibility": temporal_compatibility,
             "box_to_footprint_diagnostics": box_to_footprint_diagnostics,
             "match_evidence": evidence.match_evidence,
             "false_positive_evidence": evidence.false_positive_evidence,

backend/app/services/temporal_compatibility_service.py

@@ -0,0 +1,153 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+from datetime import UTC, datetime
+from typing import Any
+
+from app.core.errors import AppError
+from app.models import Dataset
+
+
+@dataclass(frozen=True)
+class TemporalInterval:
+    start: datetime | None
+    end: datetime | None
+    granularity: str | None
+
+    @property
+    def bounded(self) -> bool:
+        return self.start is not None and self.end is not None
+
+    def as_dict(self) -> dict[str, Any]:
+        return {
+            "start": self.start.isoformat() if self.start else None,
+            "end": self.end.isoformat() if self.end else None,
+            "granularity": self.granularity,
+        }
+
+
+class TemporalCompatibilityService:
+    @staticmethod
+    def ensure_detection_source_supported(dataset: Dataset) -> None:
+        metadata = dataset.source_metadata if isinstance(dataset.source_metadata, dict) else {}
+        if metadata.get("supports_detection") is False:
+            raise AppError(
+                code="DETECTION_SOURCE_TEMPORALLY_UNSUPPORTED",
+                message="The selected raster edition is not approved for the configured detection model",
+                details={
+                    "dataset_id": str(dataset.id),
+                    "source_name": dataset.source_name,
+                    "product_key": metadata.get("product_key"),
+                    "observed_at": TemporalCompatibilityService._iso(dataset.observed_at),
+                    "valid_from": TemporalCompatibilityService._iso(dataset.valid_from),
+                    "valid_to": TemporalCompatibilityService._iso(dataset.valid_to),
+                },
+                status_code=422,
+            )
+
+    @staticmethod
+    def assess_detection_qa(candidate: Dataset, reference: Dataset) -> dict[str, Any]:
+        candidate_interval = TemporalCompatibilityService._interval(candidate)
+        reference_interval = TemporalCompatibilityService._interval(reference)
+        candidate_historical = TemporalCompatibilityService._is_historical_detection_source(candidate)
+
+        if candidate_historical:
+            if not reference_interval.bounded:
+                TemporalCompatibilityService._raise_mismatch(
+                    candidate,
+                    reference,
+                    candidate_interval,
+                    reference_interval,
+                    "Historical imagery requires a reference dataset with an explicit compatible validity period.",
+                )
+            if not TemporalCompatibilityService._overlaps(candidate_interval, reference_interval):
+                TemporalCompatibilityService._raise_mismatch(
+                    candidate,
+                    reference,
+                    candidate_interval,
+                    reference_interval,
+                    "The historical imagery and reference dataset validity periods do not overlap.",
+                )
+
+        if (
+            candidate_interval.bounded
+            and reference_interval.bounded
+            and not TemporalCompatibilityService._overlaps(candidate_interval, reference_interval)
+        ):
+            TemporalCompatibilityService._raise_mismatch(
+                candidate,
+                reference,
+                candidate_interval,
+                reference_interval,
+                "The candidate and reference dataset validity periods do not overlap.",
+            )
+
+        return {
+            "status": "compatible",
+            "policy": "explicit_interval_overlap_for_historical_sources",
+            "candidate_dataset_id": str(candidate.id),
+            "reference_dataset_id": str(reference.id),
+            "candidate_historical": candidate_historical,
+            "candidate_interval": candidate_interval.as_dict(),
+            "reference_interval": reference_interval.as_dict(),
+        }
+
+    @staticmethod
+    def _is_historical_detection_source(dataset: Dataset) -> bool:
+        metadata = dataset.source_metadata if isinstance(dataset.source_metadata, dict) else {}
+        if metadata.get("supports_detection") is False:
+            return True
+        product_key = str(metadata.get("product_key") or "").strip().lower()
+        return dataset.source_name == "digitaal_vlaanderen_orthophoto" and product_key not in {"", "most_recent"}
+
+    @staticmethod
+    def _interval(dataset: Dataset) -> TemporalInterval:
+        start = TemporalCompatibilityService._utc(dataset.valid_from or dataset.observed_at)
+        end = TemporalCompatibilityService._utc(dataset.valid_to)
+        granularity = dataset.temporal_granularity
+
+        if start is not None and end is None and granularity == "year":
+            end = datetime(start.year, 12, 31, 23, 59, 59, tzinfo=UTC)
+        elif start is not None and end is None and granularity == "day":
+            end = start.replace(hour=23, minute=59, second=59, microsecond=999999)
+
+        return TemporalInterval(start=start, end=end, granularity=granularity)
+
+    @staticmethod
+    def _overlaps(left: TemporalInterval, right: TemporalInterval) -> bool:
+        if not left.bounded or not right.bounded:
+            return True
+        return left.start <= right.end and right.start <= left.end
+
+    @staticmethod
+    def _raise_mismatch(
+        candidate: Dataset,
+        reference: Dataset,
+        candidate_interval: TemporalInterval,
+        reference_interval: TemporalInterval,
+        message: str,
+    ) -> None:
+        raise AppError(
+            code="DETECTION_QA_TEMPORAL_MISMATCH",
+            message=message,
+            details={
+                "candidate_dataset_id": str(candidate.id),
+                "reference_dataset_id": str(reference.id),
+                "candidate_interval": candidate_interval.as_dict(),
+                "reference_interval": reference_interval.as_dict(),
+            },
+            status_code=422,
+        )
+
+    @staticmethod
+    def _utc(value: datetime | None) -> datetime | None:
+        if value is None:
+            return None
+        if value.tzinfo is None:
+            return value.replace(tzinfo=UTC)
+        return value.astimezone(UTC)
+
+    @staticmethod
+    def _iso(value: datetime | None) -> str | None:
+        normalized = TemporalCompatibilityService._utc(value)
+        return normalized.isoformat() if normalized else None

backend/tests/test_rc_detection_temporal_safety.py

@@ -0,0 +1,137 @@
+from __future__ import annotations
+
+from datetime import UTC, datetime
+from pathlib import Path
+from uuid import uuid4
+
+import pytest
+
+from app.core.errors import AppError
+from app.models import Dataset
+from app.services.temporal_compatibility_service import TemporalCompatibilityService
+
+
+ROOT = Path(__file__).parents[2]
+
+
+def dataset(
+    *,
+    dataset_type: str,
+    source_name: str,
+    observed_at: datetime | None = None,
+    valid_from: datetime | None = None,
+    valid_to: datetime | None = None,
+    temporal_granularity: str | None = None,
+    source_metadata: dict | None = None,
+) -> Dataset:
+    return Dataset(
+        id=uuid4(),
+        project_id=uuid4(),
+        name="temporal-source",
+        dataset_type=dataset_type,
+        source=source_name,
+        source_name=source_name,
+        observed_at=observed_at,
+        valid_from=valid_from,
+        valid_to=valid_to,
+        temporal_granularity=temporal_granularity,
+        source_metadata=source_metadata,
+    )
+
+
+def test_historical_orthophoto_is_rejected_for_detection() -> None:
+    historical = dataset(
+        dataset_type="raster",
+        source_name="digitaal_vlaanderen_orthophoto",
+        observed_at=datetime(2020, 1, 1, tzinfo=UTC),
+        valid_from=datetime(2020, 1, 1, tzinfo=UTC),
+        valid_to=datetime(2020, 12, 31, 23, 59, 59, tzinfo=UTC),
+        temporal_granularity="year",
+        source_metadata={"product_key": "2020", "supports_detection": False},
+    )
+
+    with pytest.raises(AppError) as exc_info:
+        TemporalCompatibilityService.ensure_detection_source_supported(historical)
+
+    assert exc_info.value.code == "DETECTION_SOURCE_TEMPORALLY_UNSUPPORTED"
+    assert exc_info.value.status_code == 422
+
+
+def test_historical_detection_qa_rejects_current_reference() -> None:
+    historical = dataset(
+        dataset_type="raster",
+        source_name="digitaal_vlaanderen_orthophoto",
+        valid_from=datetime(2020, 1, 1, tzinfo=UTC),
+        valid_to=datetime(2020, 12, 31, 23, 59, 59, tzinfo=UTC),
+        temporal_granularity="year",
+        source_metadata={"product_key": "2020", "supports_detection": False},
+    )
+    current_reference = dataset(
+        dataset_type="vector",
+        source_name="grb",
+        valid_from=datetime(2026, 7, 1, tzinfo=UTC),
+        valid_to=datetime(2026, 7, 31, 23, 59, 59, tzinfo=UTC),
+        temporal_granularity="month",
+    )
+
+    with pytest.raises(AppError) as exc_info:
+        TemporalCompatibilityService.assess_detection_qa(historical, current_reference)
+
+    assert exc_info.value.code == "DETECTION_QA_TEMPORAL_MISMATCH"
+    assert exc_info.value.status_code == 422
+
+
+def test_historical_detection_qa_accepts_overlapping_reference_edition() -> None:
+    historical = dataset(
+        dataset_type="raster",
+        source_name="digitaal_vlaanderen_orthophoto",
+        valid_from=datetime(2020, 1, 1, tzinfo=UTC),
+        valid_to=datetime(2020, 12, 31, 23, 59, 59, tzinfo=UTC),
+        temporal_granularity="year",
+        source_metadata={"product_key": "2020", "supports_detection": False},
+    )
+    historical_reference = dataset(
+        dataset_type="vector",
+        source_name="manual",
+        valid_from=datetime(2020, 6, 1, tzinfo=UTC),
+        valid_to=datetime(2020, 6, 30, 23, 59, 59, tzinfo=UTC),
+        temporal_granularity="month",
+    )
+
+    result = TemporalCompatibilityService.assess_detection_qa(historical, historical_reference)
+
+    assert result["status"] == "compatible"
+    assert result["candidate_historical"] is True
+    assert result["candidate_interval"]["start"].startswith("2020-01-01")
+    assert result["reference_interval"]["start"].startswith("2020-06-01")
+
+
+def test_current_source_with_unbounded_current_reference_remains_supported() -> None:
+    current = dataset(
+        dataset_type="raster",
+        source_name="digitaal_vlaanderen_orthophoto",
+        observed_at=datetime(2026, 7, 17, tzinfo=UTC),
+        valid_from=datetime(2026, 7, 17, tzinfo=UTC),
+        temporal_granularity="snapshot",
+        source_metadata={"product_key": "most_recent", "supports_detection": True},
+    )
+    current_reference = dataset(
+        dataset_type="vector",
+        source_name="grb",
+        observed_at=datetime(2026, 7, 16, tzinfo=UTC),
+        temporal_granularity="snapshot",
+    )
+
+    TemporalCompatibilityService.ensure_detection_source_supported(current)
+    result = TemporalCompatibilityService.assess_detection_qa(current, current_reference)
+
+    assert result["status"] == "compatible"
+    assert result["candidate_historical"] is False
+
+
+def test_detection_frontend_has_no_implicit_first_raster_fallback() -> None:
+    source = (ROOT / "frontend" / "src" / "hooks" / "useDetectionWorkflow.ts").read_text(encoding="utf-8")
+
+    assert "rasterDatasets[0]" not in source
+    assert "setSelectedDetectionDatasetId(rasterDatasets" not in source
+    assert "const datasetId = selectedDetectionDatasetId" in source

backend/tests/test_rc_runtime_observability.py

@@ -0,0 +1,31 @@
+from pathlib import Path
+
+from fastapi.testclient import TestClient
+
+from app.main import app
+
+
+ROOT = Path(__file__).parents[2]
+
+
+def test_valid_request_id_is_returned() -> None:
+    response = TestClient(app).get("/health/live", headers={"x-request-id": "rc3-check.123"})
+
+    assert response.status_code == 200
+    assert response.headers["x-request-id"] == "rc3-check.123"
+
+
+def test_unsafe_request_id_is_replaced() -> None:
+    response = TestClient(app).get("/health/live", headers={"x-request-id": "unsafe request/id"})
+
+    assert response.status_code == 200
+    assert response.headers["x-request-id"] != "unsafe request/id"
+    assert " " not in response.headers["x-request-id"]
+
+
+def test_runtime_report_is_read_only_by_default_and_requires_confirmation() -> None:
+    source = (ROOT / "scripts" / "runtime_state_report.py").read_text(encoding="utf-8")
+
+    assert '"mode": "read_only"' in source
+    assert "if args.reconcile and args.confirm != RECONCILE_CONFIRMATION" in source
+    assert "RuntimeReconciliationService.reconcile(db)" in source

backend/tests/test_sprint8_detection_foundation.py

@@ -105,6 +105,25 @@ def test_non_raster_dataset_request_is_rejected() -> None:
     assert getattr(exc_info.value, "code", None) == "INVALID_DATASET_TYPE"
 
 
+def test_historical_raster_marked_unsupported_is_rejected_before_run_creation() -> None:
+    db, project_id, dataset_id = _project_and_dataset()
+    source = db.get(Dataset, dataset_id)
+    source.source_name = "digitaal_vlaanderen_orthophoto"
+    source.source_metadata = {"product_key": "2020", "supports_detection": False}
+
+    with pytest.raises(Exception) as exc_info:
+        DetectionService.run_detection(
+            db=db,
+            project_id=project_id,
+            dataset_id=dataset_id,
+            model_id="yolo-placeholder",
+            confidence_threshold=0.5,
+        )
+
+    assert getattr(exc_info.value, "code", None) == "DETECTION_SOURCE_TEMPORALLY_UNSUPPORTED"
+    assert db.added == []
+
+
 def test_fixture_detector_persists_detections_only_with_explicit_fixture_mode() -> None:
     db, project_id, dataset_id = _project_and_dataset()
 

backend/tests/test_sprint8c_detection_visualization_qa.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import json
+from datetime import UTC, datetime
 from uuid import uuid4
 
 import pytest
@@ -11,7 +12,7 @@ from shapely.geometry import Polygon, box
 from app.core.errors import AppError
 from app.main import app
 from app.db.session import get_db
-from app.models import AnalysisRun, Dataset, Detection, Job, Metric, Project, QualityCheck, VectorFeature
+from app.models import AnalysisRun, Dataset, Detection, Metric, QualityCheck, VectorFeature
 from app.services.detection_service import DetectionService
 
 
@@ -89,6 +90,17 @@ def _detection(project_id, dataset_id, analysis_run_id, class_name="building", c
     )
 
 
+def _source_dataset(project_id, dataset_id):
+    return Dataset(
+        id=dataset_id,
+        project_id=project_id,
+        name="source.tif",
+        dataset_type="raster",
+        source="manual",
+        source_name="manual",
+    )
+
+
 def test_detection_geojson_feature_collection_shape() -> None:
     project_id = uuid4()
     dataset_id = uuid4()
@@ -206,6 +218,7 @@ def test_detection_qa_persists_quality_check_and_metrics() -> None:
     db = FakeSession(
         objects={
             (AnalysisRun, analysis_run_id): AnalysisRun(id=analysis_run_id, project_id=project_id, dataset_id=dataset_id, analysis_type="detection", status="success", parameters_json={}),
+            (Dataset, dataset_id): _source_dataset(project_id, dataset_id),
             (Dataset, reference_dataset_id): reference_dataset,
         },
         query_rows={Detection: [detection], VectorFeature: [reference_feature]},
@@ -227,6 +240,8 @@ def test_detection_qa_persists_quality_check_and_metrics() -> None:
     assert result["quality_check_id"] == str(quality_checks[0].id)
     assert quality_checks[0].analysis_run_id == analysis_run_id
     assert quality_checks[0].reference_dataset_id == reference_dataset_id
+    assert quality_checks[0].parameters_json["temporal_compatibility"]["status"] == "compatible"
+    assert quality_checks[0].findings_json["temporal_compatibility"]["status"] == "compatible"
     assert [metric.metric_key for metric in metrics] == [
         "precision",
         "recall",
@@ -237,6 +252,53 @@ def test_detection_qa_persists_quality_check_and_metrics() -> None:
     ]
 
 
+def test_detection_qa_rejects_non_overlapping_historical_reference_editions() -> None:
+    project_id = uuid4()
+    dataset_id = uuid4()
+    reference_dataset_id = uuid4()
+    analysis_run_id = uuid4()
+    source_dataset = _source_dataset(project_id, dataset_id)
+    source_dataset.source_name = "digitaal_vlaanderen_orthophoto"
+    source_dataset.source_metadata = {"product_key": "2020", "supports_detection": False}
+    source_dataset.valid_from = datetime(2020, 1, 1, tzinfo=UTC)
+    source_dataset.valid_to = datetime(2020, 12, 31, 23, 59, 59, tzinfo=UTC)
+    reference_dataset = Dataset(
+        id=reference_dataset_id,
+        project_id=project_id,
+        name="current-grb.geojson",
+        dataset_type="vector",
+        source="grb",
+        source_name="grb",
+        dataset_role="reference",
+        valid_from=datetime(2026, 7, 1, tzinfo=UTC),
+        valid_to=datetime(2026, 7, 31, 23, 59, 59, tzinfo=UTC),
+    )
+    db = FakeSession(
+        objects={
+            (AnalysisRun, analysis_run_id): AnalysisRun(
+                id=analysis_run_id,
+                project_id=project_id,
+                dataset_id=dataset_id,
+                analysis_type="detection",
+                status="success",
+                parameters_json={},
+            ),
+            (Dataset, dataset_id): source_dataset,
+            (Dataset, reference_dataset_id): reference_dataset,
+        },
+    )
+
+    with pytest.raises(AppError) as exc_info:
+        DetectionService.compare_detections_with_reference(
+            db=db,
+            analysis_run_id=analysis_run_id,
+            reference_dataset_id=reference_dataset_id,
+        )
+
+    assert exc_info.value.code == "DETECTION_QA_TEMPORAL_MISMATCH"
+    assert db.added == []
+
+
 def test_detection_qa_no_match_case_persists_zero_scores() -> None:
     project_id = uuid4()
     dataset_id = uuid4()
@@ -260,6 +322,7 @@ def test_detection_qa_no_match_case_persists_zero_scores() -> None:
     db = FakeSession(
         objects={
             (AnalysisRun, analysis_run_id): AnalysisRun(id=analysis_run_id, project_id=project_id, dataset_id=dataset_id, analysis_type="detection", status="success", parameters_json={}),
+            (Dataset, dataset_id): _source_dataset(project_id, dataset_id),
             (Dataset, reference_dataset_id): reference_dataset,
         },
         query_rows={Detection: [detection], VectorFeature: [reference_feature]},
@@ -311,6 +374,7 @@ def test_configured_yolo_qa_requires_persisted_tile_manifest_provenance() -> Non
                 model_name="yolo-configured",
                 parameters_json={"model_id": "yolo-configured"},
             ),
+            (Dataset, dataset_id): _source_dataset(project_id, dataset_id),
             (Dataset, reference_dataset_id): reference_dataset,
         },
         query_rows={Detection: [detection], VectorFeature: [reference_feature]},
@@ -391,6 +455,7 @@ def test_detection_qa_excludes_references_outside_persisted_tile_coverage(tmp_pa
                     "tile_manifest_path": str(manifest_path),
                 },
             ),
+            (Dataset, dataset_id): _source_dataset(project_id, dataset_id),
             (Dataset, reference_dataset_id): reference_dataset,
         },
         query_rows={Detection: [detection], VectorFeature: [inside_reference, outside_reference]},
@@ -452,6 +517,7 @@ def test_detection_qa_reports_box_to_footprint_diagnostic_without_changing_stric
                     "tile_manifest_path": str(manifest_path),
                 },
             ),
+            (Dataset, dataset_id): _source_dataset(project_id, dataset_id),
             (Dataset, reference_dataset_id): reference_dataset,
         },
         query_rows={Detection: [detection], VectorFeature: [reference_feature]},

docs/CODEX_EXECUTION_LOG.md

@@ -36,6 +36,27 @@
 - Local Docker CLI is unavailable on the Windows Codex host. Docker config,
   image build, live health truthfulness, backup and restore are therefore
   scheduled on the Docker-enabled Tower after push.
+- Pushed and deployed commit `9c402e0`; subsequently pushed the cwd-independent
+  backup fix `38a3bd0` and secret rotation command `fc42ea9`.
+- Tower Docker config, all-in-one build, live migration smoke and browser
+  runtime smoke passed. `/health/live` and `/health/ready` report `ok`,
+  PostGIS 3.6, Alembic `202607160001`, writable storage and configured YOLO.
+- Startup reconciliation changed five impossible orphaned jobs and two
+  analysis runs to terminal `failed` state with `PROCESS_INTERRUPTED`; no
+  `running` rows remain.
+- Created the full SHA-256 inventory backup
+  `rc-belgium-north-sea-38a3bd0`, verified it read-only and restored it in an
+  isolated temporary database. The first restore attempt exposed stale glibc
+  collation metadata in `template1`/`postgres`; those empty system databases
+  were reindexed and refreshed after the backup, then restore passed.
+- Rotated the production PostgreSQL password with a generated 256-bit value
+  without logging it, atomically updated the Tower `.env` and recreated the
+  healthy container.
+- Created the current secure backup
+  `rc-belgium-north-sea-fc42ea9-secure` (1.4 GiB), verified all checksums and
+  repeated isolated restore. PostGIS/Alembic and all retained critical table
+  counts match; the temporary database was removed.
+- RC-1 and RC-2 are complete. RC-3 is active.
 
 ## Sprint 229 - Governed ALZ definitive release promotion (2026-07-17)
 
@@ -10340,3 +10361,36 @@ Validation:
   TypeScript typecheck and the production Vite build.
 - Tower deployment and browser acceptance results are recorded after the
   rebuilt all-in-one runtime is verified.
+## 2026-07-17 - Belgium/North Sea RC-3 local gate
+
+- Removed automatic selection and every `rasterDatasets[0]` execution fallback
+  from Detection Lab. Normal detection, guided preparation and calibration now
+  require an explicit raster selection.
+- Added `TemporalCompatibilityService`. Official raster editions carrying
+  `supports_detection=false` fail before Job/AnalysisRun creation with
+  `DETECTION_SOURCE_TEMPORALLY_UNSUPPORTED`.
+- Detection QA now loads the persisted source Dataset and rejects historical
+  candidate/reference periods that are absent or non-overlapping with
+  `DETECTION_QA_TEMPORAL_MISMATCH`.
+- Compatible temporal evidence is persisted under
+  `parameters_json.temporal_compatibility` and
+  `findings_json.temporal_compatibility` on the existing QualityCheck.
+- Added sanitized request IDs, request-duration logs and correlated detection
+  start/QA completion logs.
+- Added `scripts/runtime_state_report.py`; default mode is read-only and
+  mutation requires `--reconcile --confirm reconcile-interrupted-runtime`.
+
+Validation:
+
+- `python -m compileall backend/app`: passed.
+- `python -m pytest backend`: 974 passed.
+- `npm run typecheck`: passed.
+- `npm run build`: passed.
+- `bash scripts/run_readiness_check.sh`: passed, including 122-route API audit,
+  974 tests, Alembic head, typecheck and build.
+- `python -m alembic heads`: one head, `202607160001`.
+- `python -m alembic upgrade head --sql`: passed.
+- backup/restore/live-smoke shell syntax checks: passed.
+- Local `docker compose config` was unavailable because this Windows
+  workstation has no Docker CLI; Tower validation remains mandatory before
+  RC-3 completion.

docs/RC_ROADMAP_BELGIUM_NORTH_SEA.md

@@ -144,9 +144,9 @@ editions and licences must still pass source-specific probes before activation.
 | Phase | State | Purpose |
 | --- | --- | --- |
 | RC-0 | complete | freeze scope and produce release evidence baseline |
-| RC-1 | in progress | backup, restore and data safety |
-| RC-2 | verification pending | health, capabilities and stale-runtime correctness |
-| RC-3 | pending | temporal detection/QA correctness and observability |
+| RC-1 | complete | backup, restore and data safety |
+| RC-2 | complete | health, capabilities and stale-runtime correctness |
+| RC-3 | in progress | temporal detection/QA correctness and observability |
 | RC-4 | pending | national/maritime scope and provider coverage contracts |
 | RC-5 | pending | deployment, secrets, configuration, fresh install and rollback |
 | RC-6 | pending | complete CI, dependency and supply-chain gates |
@@ -190,6 +190,12 @@ Runtime evidence is stored outside Git under `storage/release-evidence/`.
 
 ## RC-1 - Backup, restore and data safety
 
+**State: complete.** Tower retains the checksum-verified 1.4 GiB backup
+`rc-belgium-north-sea-fc42ea9-secure`. Its manifest records a non-default
+database password. An isolated restore reached PostGIS 3.6 and Alembic
+`202607160001`, reconciled every retained critical table count and removed the
+temporary database.
+
 ### Work
 
 - Add a safe production backup command for PostgreSQL custom-format dumps.
@@ -219,8 +225,11 @@ Runtime evidence is stored outside Git under `storage/release-evidence/`.
 
 ## RC-2 - Truthful runtime state
 
-**State: implementation complete, live verification pending.** Local compile,
-963 backend tests, frontend typecheck/build and the full readiness gate pass.
+**State: complete.** Local compile, 963 backend tests, frontend
+typecheck/build and the full readiness gate pass. Tower reports green
+DB/PostGIS/migration/storage readiness and configured YOLO capability. Startup
+reconciled five orphaned jobs and two orphaned analysis runs; zero remain
+`running`.
 
 ### Work
 
@@ -253,6 +262,11 @@ Runtime evidence is stored outside Git under `storage/release-evidence/`.
 
 ## RC-3 - Temporal QA correctness and observability
 
+**State: implementation complete; live deployment acceptance pending.** The
+local release gate passes backend compilation, all 974 backend tests, frontend
+typecheck/build, the integrated readiness script, one Alembic head and complete
+offline migration SQL generation.
+
 ### Work
 
 - Stop Detection Lab from silently selecting the first raster.

docs/ROLLBACK_AND_RECOVERY.md

@@ -32,3 +32,10 @@ Storage and model files are inventoried rather than copied into the database
 dump. Release backups must therefore be paired with the persistent storage
 volume backup policy. Use `--inventory-mode sha256` for final release
 evidence.
+
+An old persistent volume can also retain glibc collation metadata for the
+empty `postgres` and `template1` system databases. If `createdb` fails for that
+reason, first complete and verify the production backup, then reindex each
+affected system database and run `ALTER DATABASE <name> REFRESH COLLATION
+VERSION`. Never refresh before reindexing, and never treat this maintenance as
+a substitute for the isolated restore proof.

docs/TODO.md

@@ -10,9 +10,9 @@ maritieme zones.
 - [x] RC-0: Belgische en maritieme scopefreeze vastleggen.
 - [x] RC-0: autonome roadmap zonder afzonderlijke RC-12 vastleggen.
 - [x] RC-0: deterministisch release-evidence manifest implementeren en draaien.
-- [ ] RC-1: actuele productiebackup, verificatie en geisoleerde restore bewijzen.
-- [ ] RC-2: liveness/readiness/capabilities fail-closed en waarheidsgetrouw maken.
-- [ ] RC-2: verweesde jobs en analysis runs na een procesherstart verzoenen.
+- [x] RC-1: actuele productiebackup, verificatie en geisoleerde restore bewijzen.
+- [x] RC-2: liveness/readiness/capabilities fail-closed en waarheidsgetrouw maken.
+- [x] RC-2: verweesde jobs en analysis runs na een procesherstart verzoenen.
 - [ ] RC-3: expliciete rasterkeuze en temporeel compatibele detectie-QA afdwingen.
 - [ ] RC-4: nationale basisdekking, Wallonie, Brussel en Belgische Noordzee via
   beheerde providers en golden areas operationaliseren.

frontend/src/hooks/useDetectionWorkflow.ts

@@ -1,4 +1,4 @@
-import { useEffect, useState } from 'react'
+import { useState } from 'react'
 import { datasetsApi, detectionApi } from '../services/api'
 import type {
   DatasetCreateResponse,
@@ -126,12 +126,6 @@ export function useDetectionWorkflow({
   const [detectionCalibrationError, setDetectionCalibrationError] = useState<string | null>(null)
   const [detectionWorkflowStage, setDetectionWorkflowStage] = useState<DetectionWorkflowStage>('idle')
 
-  useEffect(() => {
-    if (!selectedDetectionDatasetId && rasterDatasets.length > 0) {
-      setSelectedDetectionDatasetId(rasterDatasets[0].id)
-    }
-  }, [rasterDatasets, selectedDetectionDatasetId])
-
   const loadDetectionModels = async () => {
     setLoadingDetectionModels(true)
     setDetectionModelError(null)
@@ -259,7 +253,7 @@ export function useDetectionWorkflow({
       setDetectionRunError('Select a project first')
       return
     }
-    const datasetId = selectedDetectionDatasetId || rasterDatasets[0]?.id
+    const datasetId = selectedDetectionDatasetId
     if (!datasetId) {
       setDetectionRunError('Select a raster dataset')
       return
@@ -317,7 +311,7 @@ export function useDetectionWorkflow({
       setDetectionRunError('De regionale werkruimte is nog niet geladen')
       return null
     }
-    const datasetId = datasetIdOverride || selectedDetectionDatasetId || rasterDatasets[0]?.id
+    const datasetId = datasetIdOverride || selectedDetectionDatasetId
     if (!datasetId) {
       setDetectionRunError('Kies of voeg eerst een gegeorefereerd luchtbeeld toe')
       return null
@@ -446,7 +440,7 @@ export function useDetectionWorkflow({
       setDetectionCalibrationError('Select a project before calibration')
       return
     }
-    const datasetId = selectedDetectionDatasetId || rasterDatasets[0]?.id
+    const datasetId = selectedDetectionDatasetId
     if (!datasetId) {
       setDetectionCalibrationError('Select a raster dataset before calibration')
       return

scripts/README.md

@@ -4,6 +4,25 @@ Setup-, import-, demo- en maintenance-scripts voor GeoIntel.
 
 ## Runtime verification
 
+Inspect interrupted runtime state without changing it:
+
+```bash
+python scripts/runtime_state_report.py
+```
+
+Only after reviewing that report, explicitly reconcile records that can no
+longer be running:
+
+```bash
+python scripts/runtime_state_report.py \
+  --reconcile \
+  --confirm reconcile-interrupted-runtime
+```
+
+The default mode is read-only. Reconciliation only marks currently `running`
+jobs and analysis runs as failed with `PROCESS_INTERRUPTED`; it does not delete
+jobs, results, datasets or artifacts.
+
 Audit the active backend route surface against `docs/API_CONTRACTS.md`:
 
 ```bash

scripts/runtime_state_report.py

@@ -0,0 +1,84 @@
+#!/usr/bin/env python3
+"""Report stale runtime records and optionally reconcile them explicitly."""
+
+from __future__ import annotations
+
+import argparse
+import json
+import sys
+from pathlib import Path
+
+
+ROOT = Path(__file__).resolve().parents[1]
+BACKEND = ROOT / "backend"
+sys.path.insert(0, str(BACKEND))
+
+from app.db.session import SessionLocal  # noqa: E402
+from app.models import AnalysisRun, Job  # noqa: E402
+from app.services.runtime_reconciliation_service import RuntimeReconciliationService  # noqa: E402
+
+
+RECONCILE_CONFIRMATION = "reconcile-interrupted-runtime"
+
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument(
+        "--reconcile",
+        action="store_true",
+        help="Mark running jobs and analysis runs as failed with PROCESS_INTERRUPTED.",
+    )
+    parser.add_argument(
+        "--confirm",
+        default="",
+        help=f"Required with --reconcile: {RECONCILE_CONFIRMATION}",
+    )
+    return parser.parse_args()
+
+
+def main() -> int:
+    args = parse_args()
+    if args.reconcile and args.confirm != RECONCILE_CONFIRMATION:
+        print(
+            json.dumps(
+                {
+                    "status": "refused",
+                    "reason": "Explicit reconciliation confirmation is missing.",
+                    "required_confirmation": RECONCILE_CONFIRMATION,
+                },
+                indent=2,
+            )
+        )
+        return 2
+
+    with SessionLocal() as db:
+        running_jobs = db.query(Job).filter(Job.status == "running").order_by(Job.created_at).all()
+        running_runs = (
+            db.query(AnalysisRun)
+            .filter(AnalysisRun.status == "running")
+            .order_by(AnalysisRun.created_at)
+            .all()
+        )
+        result = {
+            "status": "ok",
+            "mode": "read_only",
+            "running_job_count": len(running_jobs),
+            "running_analysis_run_count": len(running_runs),
+            "running_job_ids": [str(item.id) for item in running_jobs],
+            "running_analysis_run_ids": [str(item.id) for item in running_runs],
+        }
+        if args.reconcile:
+            reconciled = RuntimeReconciliationService.reconcile(db)
+            result.update(
+                {
+                    "mode": "reconciled",
+                    "interrupted_jobs": reconciled.interrupted_jobs,
+                    "interrupted_analysis_runs": reconciled.interrupted_analysis_runs,
+                }
+            )
+        print(json.dumps(result, indent=2))
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())