Classify operator background corpus

docs/AI_PIPELINES.md

@@ -247,6 +247,7 @@ considered as a default:
 
 ```bash
 OPERATOR_SAMPLE_MANIFEST_PATH=storage/operator-data/operator_samples_manifest.json \
+OPERATOR_BACKGROUND_CATEGORIES="pure_empty_negative" \
 OPERATOR_BACKGROUND_SAMPLE_SLUGS="postel_bos lommel_heide kasterlee_bos" \
 QUALITY_MODEL_ASSET_IDS="geointel-building-yolov8n-expanded160e50-pt geointel-building-yolov8n-tile30-pt yolov8s-building-segmentation-pt" \
 QUALITY_TILE_SIZES="640" \
@@ -257,8 +258,13 @@ bash scripts/run_operator_hard_negative_detection_matrix.sh http://192.168.10.15
 
 The hard-negative matrix uploads only background rasters and counts detections
 as false-positive pressure. It does not run QA/QC or invent reference metrics
-for empty/sparse background AOIs. The first expanded local model improved dense
-AOI F1, but Kasterlee-bos false positives block default promotion.
+for empty/sparse background AOIs. Operator manifests classify background
+samples as `pure_empty_negative` when GRB returns zero reference buildings and
+`sparse_building_context` when contextual buildings are present. Use
+`OPERATOR_BACKGROUND_CATEGORIES="pure_empty_negative"` for default-promotion
+hard-negative gates, then run `sparse_building_context` as a separate review
+matrix. The first expanded local model improved dense AOI F1, but Kasterlee-bos
+false positives block default promotion.
 
 The current inactive AOI1024 background-aware local model asset,
 `geointel-building-yolov8s-aoi1024bg512r3e50-pt`, is exposed in Detection Lab