Add detection model promotion report

scripts/README.md

@@ -551,6 +551,24 @@ Tower-local model evaluation status:
 - Do not silently activate this model as a default. Apply it only as an explicit
   operator choice until the model catalog/threshold workflow is hardened.
 
+Build a model promotion decision report from an existing positive-AOI evidence
+portfolio and one or more hard-negative/background summaries:
+
+```bash
+python scripts/build_detection_model_promotion_report.py \
+  --positive-portfolio /mnt/user/appdata/geointel/artifacts/detection-calibration-portfolio/positive-aoi-expanded-20260708/output/calibration_evidence_portfolio.json \
+  --hard-negative-summary /mnt/user/appdata/geointel/artifacts/detection-hard-negatives/hardneg160r8e40-live/hard_negative_matrix_summary.json \
+  --output-dir /mnt/user/appdata/geointel/artifacts/detection-model-promotion/expanded-positive-vs-hard-negative-20260708
+```
+
+The report writes `detection_model_promotion_report.json` and
+`detection_model_promotion_report.md`. It groups candidates by
+`model_asset_id`, tile size, tile overlap and confidence threshold, then applies
+explicit gates for positive-AOI sample count, background sample count, mean F1
+and maximum background detections per sample. It is evidence/report tooling
+only: it does not run inference, mutate application data, download models or
+change the active YOLO configuration.
+
 Clean old offline demo export artifacts without touching uploaded source data:
 
 ```bash