fix(results): gate operational AI exports on QA
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@@ -2220,10 +2220,34 @@ Detection run export request:
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{
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"export_kind": "detection_run",
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"analysis_run_id": "uuid",
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"intended_use": "review",
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"name": "optional-basename"
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}
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```
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`intended_use` is `review` by default. Every detection FeatureCollection and
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export record contains a machine-readable `geointel_result` / `result_trust`
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contract. Raw model output remains `authoritative: false` and is classified as
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`unverified_ai_review_output` when authoritative QA is absent or incomplete.
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Feature properties repeat the classification so it survives GIS workflows
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that discard collection-level metadata.
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`intended_use: operational` fails closed with
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`DETECTION_OPERATIONAL_EXPORT_BLOCKED` unless the same persisted run has a
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completed detection-versus-reference check that proves all of the following:
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- the reference Dataset is authoritative and specifically approved as primary
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authority for building validation;
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- inference coverage was derived from the persisted tile-manifest union;
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- imagery/reference time compatibility is proven;
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- geometry is supported and no QA warnings remain;
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- false-positive and false-negative counts are both explicitly present and
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zero.
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Even a passing operational export remains AI-derived and therefore retains
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`authoritative: false`, the exact quality-check/reference identifiers and an
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operator-review limitation. Model confidence by itself never unlocks export.
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Segmentation run export request:
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```json
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@@ -2251,7 +2275,10 @@ Response persists an `exports` row and writes a deterministic JSON artifact:
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Vector dataset exports use the stored dataset GeoJSON. Detection and
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segmentation exports use persisted first-class geometry records and the
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existing Detection/Segmentation GeoJSON conversion services. Vector selection
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existing Detection/Segmentation GeoJSON conversion services. Detection export
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in the frontend is deliberately labelled as a control layer and requests
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`intended_use: review`; it cannot silently produce an operationally approved
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artifact. Vector selection
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exports query persisted PostGIS `vector_features` with the supplied EPSG:4326
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bbox, write the selected FeatureCollection as a `vector_selection_geojson`
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artifact, and persist bbox/feature-count metadata in the export record. When
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