Use split background reports in promotion gate

docs/AI_PIPELINES.md

@@ -260,6 +260,24 @@ The split runner writes `background_corpus_split_summary.json` and Markdown
 handoff output with a strict `pure_empty_negative` gate and a separate
 review-only `sparse_building_context` block.
 
+Use that split summary directly in the model promotion report:
+
+```bash
+python scripts/build_detection_model_promotion_report.py \
+  --positive-portfolio artifacts/detection-quality-matrix/multi-sample/aoi1024bg512r3e50-positive/multi_sample_quality_summary.json \
+  --background-split-summary artifacts/detection-hard-negatives/aoi1024bg512r3e50-split/background_corpus_split_summary.json \
+  --output-dir artifacts/detection-model-promotion/aoi1024bg512r3e50-split-aware \
+  --min-positive-samples 7 \
+  --min-background-samples 2 \
+  --min-mean-f1 0.25 \
+  --max-background-detections-per-sample 0
+```
+
+The promotion report follows the split contract: `pure_empty_negative` is the
+only strict background gate for default promotion, while
+`sparse_building_context` remains review-only evidence in the report. This keeps
+contextual buildings from being treated as empty-background false positives.
+
 The underlying single-category matrix remains available:
 
 ```bash