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- Add reproducible v6 boundary, blessing, and consensus-adjudication corpora, plus the tiny-transformer trainer and v6 release-gate evaluator that gate every candidate on the deployed baselines. - Wire consensus-label merging, product-policy anchor evaluation, and sealed blessing benchmark review with their pytest coverage. - Refresh open-training corpus generation, iterative retraining runner, and random-holdout evaluation so v6 candidates can be benchmarked end-to-end.
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Clipboard semantic evidence adjudication v3
Review only the fields listed in unresolvedFields. Judge from the text itself;
do not inspect previous model votes, source labels, or another adjudicator.
Apply labeling-instructions-v4.md.
Return one JSON object per input record using the exact schema defined in
adjudication-instructions-v2.md.
For compatibility, recordDisposition remains keep or
exclude-device-command. In v3, exclude-device-command also covers generic
search, system/account queries, and other clearly virtual-assistant-only text.
It does not cover real-world service requests, named-recipient communication
with content, or private/shared-context interpersonal questions.
Requirements:
- Evidence must be a short exact quote copied from the input text.
resolutions,confidence, andevidencemust contain exactly the fields inunresolvedFields.- Use
unknownrather than inventing context for low-information fragments. - Confidence is per field and must be between 0 and 1.
- Do not output explanations, markdown, or additional fields.