Target related hard-negative contexts
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@@ -113,6 +113,12 @@ The deterministic cap removes only repeated entries and retains every unique
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train tile at least once; manifests record pre-cap counts, final counts and the
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number of dropped repeats. This keeps a weak region prominent without turning
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the national detector into a single-region expert.
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Precision correction expands failed semantic contexts into related negative
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families: coastal urban failures target port/dunes negatives, industrial
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failures target industrial/rail/port negatives, and ribbon/rural/regional
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architecture failures target their governed farmland, forest or quarry
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counterparts. These diagnostic negative repeats are ordered ahead of generic
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repeats so the regional cap cannot discard them first.
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The checkpointed orchestrator invokes this builder after every rejected
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iteration, stores its checksum in `training-loop-state.json`, and uses the
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resulting dataset YAML for the next checkpoint. A restart resumes both the
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