MUSE 6-axis unlearning verifier

Description

Six-axis verifier for unlearning and deletion claims: verbatim, knowledge, privacy, bias, utility, and scalability.

Technical signature

in: (model_pre, model_post, target_set) → out: { axis_scores{6}, claim_supported }

Adversarial robustness

Detects shallow unlearning via knowledge-axis residue.

Daubert eligibility

Method is peer-reviewed, has published error rates, and is reproducible from the chain-of-custody hash. Eligible for Tier-A admissibility packaging. Ultimate admissibility is the court's determination.