44 lines
1.5 KiB
Markdown
44 lines
1.5 KiB
Markdown
# Selector
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This folder contains rule-based selector configuration and examples.
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The v0.2 selector should not call an LLM.
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It should use simple matching rules:
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- Trigger keywords
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- Input types
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- Negative triggers
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- Pipeline position
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- Selection priority
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- Negative trigger first
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- No-call threshold
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- QPI-before-IA gate
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- QPI positive-signal gate
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- Direct-execution no-call signals
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- Calibration smoke checks
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Current files:
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- `selector_rules.json`
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- `selector_examples.json`
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- `selector_calibration_inputs.json`
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- `qpi_case_digests.json`
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The selector does not call an LLM.
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The executable demo is `scripts/run_selector_demo.py`.
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Selector regression is `scripts/run_selector_regression.py`.
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Selector calibration smoke check is `scripts/run_selector_calibration_smoke.py`.
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`qpi_case_digests.json` stores owner-reviewed QPI case digests that can feed selector calibration or later regression selection. It is not a model status upgrade and should not include unreviewed draft cases.
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Digest field notes:
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- `misclassification_risk` is the canonical digest field matching QPI's structured output contract.
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- `qpi_complexity_pattern` records judgment complexity: `not_mixed`, `intra_frame_mixed`, or `inter_viewpoint_divergence`.
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- `qpi_complexity_pattern=intra_frame_mixed` does not imply `classification=mixed`; `classification` is the final routing class, while `qpi_complexity_pattern` records the structure of the judgment.
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- Multi-perspective / inter-viewpoint cases require `classification_by_viewpoint` or `viewpoint_summary`.
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