Rotate capped training samples across iterations

docs/CODEX_EXECUTION_LOG.md

@@ -11933,6 +11933,17 @@ Verified:
   AI-assisted inspection found labels aligned with visible roof footprints and
   retained the deliberately sparse hard-negative contexts.
 - NVIDIA preflight: RTX 4080 SUPER idle and available before the v43 handoff.
+- Iteration 2 selected its epoch-5 checkpoint, reached aggregate calibration F1
+  `0.584` and zero pure-empty detections, but remained closed because Flanders
+  F1/precision/recall and Wallonia precision failed. Iteration 3 started from
+  the exact rejected checkpoint without opening test/background.
+- Confirmed Ultralytics preserves duplicate paths from the 4,077-entry
+  failure-driven list. Added deterministic per-round rotation of the repeats
+  retained by the 65% regional cap, preventing persistent identical failures
+  from producing an identical capped list forever while preserving every
+  unique train tile and all protected-split exclusions.
+- `py -3 -m pytest -q backend/tests/test_failure_driven_yolo_sampling.py backend/tests/test_belgium_training_loop.py`
+  (`20 passed`).
 
 Open: