What does this equation mean?

A useful, explicitly illustrative way to see the size of that gap is to price coverage directly as a scenario, not a reported figure: $C_{\mathrm{cov}}(D) = D \cdot h \cdot w$. the cost of testing D domains to an adequate depth h (in expert-hours per domain) at a specialist wage w . Anchoring h at roughly 150 hours, taken from Anthropic’s single-domain biosecurity effort, and w at a conservative 50 to 100 US dollars an hour for domain expertise — well below typical consulting rates for the specialists these programmes actually recruit — testing even fifty domains to that depth, a small number next to the realistic combination of languages, deployment surfaces, and misuse categories a deployed model faces, comes to roughly 375,000 to 750,000 US dollars in labour alone for a single testing pass, before any of the iterative retesting that a model updated on any cadence would require. That is a back-of-envelope scenario built from the two anchor figures above, not a cost any lab has published, and it should be read as illustrating the shape of the problem rather than as a documented number: coverage costs scale with the product of domains and depth, both of which the attack surface of a general-purpose model pushes upward faster than any red-teaming budget has grown to match.