Document YOLOv8s benchmark status
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- Segmentation now distinguishes configured model state from UI-runnable state and blocks the explicit test/demo-only fixture segmenter in the normal run form.
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- Added regression coverage for AI Lab action guardrails and compact guardrail styling.
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- No API contracts, migrations, product capabilities, live provider fetching or AI/model dependency changes were introduced.
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## Operator YOLOv8s hard-negative benchmark (2026-07-08)
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- Trained a Tower-local YOLOv8s hard-negative building detector from the existing operator tile dataset.
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- Published the trained runtime artifact as `geointel-building-yolov8s-hardneg160r4e50-pt` in the live model asset catalog without adding application download behavior.
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- Reused persisted dense QA and hard-negative benchmark runs through the existing live API.
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- Observed dense QA F1 scores up to `0.6380` and safest current threshold behavior around `0.25`.
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- Kept the model inactive by default because the `kasterlee_bos` hard-negative sample still produced 10 detections at threshold `0.25`.
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- No repository code, API contracts, migrations, product behavior, provider fetching or AI dependency strategy changed in this benchmark pass.
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