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https://github.com/ruvnet/RuView
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Claude
2aac160067
New ruvector module: anonymized ProfileStore (one-way SHA-256 hashed tags, safe-session scores only), deterministic exact kNN, cohort warm-start (a new person's optimizer seeded from the k nearest responders as down-weighted GP pseudo-observations), physiological drift detection (Welford centroid with stimulus-input fields masked out of the distance), and deterministic k-means response clustering. Honesty guarantees, asserted in tests: cohort priors carry >=25x the real-observation noise, are excluded from the EI incumbent, the audit log, and the clinician report — borrowed expectations never masquerade as this person's measured response. The GP gains per-observation noise; the real path is arithmetically unchanged (pinned witness 13cb164c... preserved). Governor wiring: seed_from_cohort, export_anonymized_profile, per-session drift_status. Integration tests: cohort warm-start beats the cold 40 Hz prior for a detuned subject; collapsed physiology flags Drifted. Crate: 75 tests + 1 doctest. Workspace gate: 2,876 passed, 0 failed. Benches: kNN/500 profiles ~15us, warm-start ~16us; no regression on existing paths (recommend ~15us, calibration sweep ~111us). https://claude.ai/code/session_01MjBucx95K4BuUxZi8NWwRH