Balance YOLO label QA coverage

scripts/README.md

@@ -488,7 +488,10 @@ The renderer writes `operator_yolo_label_qa_summary.json`,
 existing YOLO labels on existing tile images only; it does not run inference,
 train a model, fetch providers or create fake detections. Missing image files,
 missing label files, invalid YOLO rows and low-variance/blank-looking rendered
-tiles are reported in the JSON/Markdown artifacts.
+tiles are reported in the JSON/Markdown artifacts. Selection is balanced by
+`sample_slug` before taking additional high-density tiles, so one dense urban
+AOI cannot hide the other source samples from visual review. The report records
+`selected_sample_count` and `selected_sample_slugs` for coverage evidence.
 
 Current Tower audit status:
 
@@ -518,6 +521,15 @@ Current Tower audit status:
   available but inactive. The split-aware promotion report rejected all tested
   thresholds: `0.25` and `0.35` passed the pure-empty background gate but had
   mean F1 below `0.25`; `0.15` also failed the pure-empty false-positive gate.
+- `yolo-building-aoi1024-expanded-minpx4vis035`: expanded small-building
+  recovery dataset with 20 source AOIs, 171 retained tiles, 45,892 labels,
+  144 train tiles, 27 validation tiles and 9 low-variance negatives removed.
+  Its configured audit passed with no warnings, median normalized box area
+  `0.000694274766`, small-box share `0.3832694151486098`, no invalid labels and
+  no missing label files. The balanced visual pass rendered 40 tiles across all
+  19 source samples that retained at least one tile, with no invalid labels,
+  missing images or low-variance selections. A new candidate may be trained,
+  but remains inactive until positive and split-background promotion gates pass.
 
 After rebuilding the all-in-one image, the operator scripts are available inside
 the container at `/app/scripts/...`. Before rebuilding, use the host checkout or