--- name: wmdp-eval description: Audit a dual-use capability claim against WMDP, unlearning evaluation, and elicitation studies. version: 1.0.0 phase: 18 lesson: 17 tags: [wmdp, rmu, dual-use, biosecurity, cybersecurity, chemistry] --- Given a dual-use capability claim ("our model does not meaningfully help with bioweapons / cyberattack / chemistry"), audit the supporting evaluation. Produce: 1. Benchmark coverage. Was WMDP (or an equivalent yellow-zone benchmark) run? Report per-domain scores (bio, cyber, chem). A claim without per-domain numbers cannot be evaluated. 2. Unlearning trace. If unlearning was applied (RMU or alternative), report the general-capability delta (MMLU, HELM, HumanEval). Unlearning with no general-capability report is not credible. 3. Refusal-path-audit. Was the benchmark administered via raw completion or via the production safety stack? A model that scores low only because of the safety stack is still dual-use capable when the stack is bypassed. 4. Elicitation study. Multiple-choice capability does not equal elicitation-hardened capability. Are Anthropic-style acquisition trials, or equivalent novice-in-the-loop studies, referenced? If not, the claim is limited to WMDP-style evidence. 5. Novice-vs-expert split. Novice-relative uplift and expert-absolute capability are different quantities. Are both addressed? Hard rejects: - Any dual-use safety claim without WMDP-equivalent capability measurement. - Any unlearning claim without general-capability delta. - Any "no meaningful uplift" claim without novice-in-the-loop study. Refusal rules: - If the user asks whether their model crosses ASL-3, refuse a direct answer; the thresholds are lab-specific (Lesson 18) and elicitation-dependent. - If the user asks for a WMDP cutoff that is "safe," refuse — the threshold depends on elicitation resistance, tacit-knowledge barriers, and the deployment surface. Output: a one-page audit that fills the five sections above, flags the most important missing evidence, and identifies whether the claim is WMDP-level or deployment-level. Cite Li et al. (arXiv:2403.03218) once as the benchmark source.