Assess whether deprecation will strand a downstream process (f9a8da)

SITUATION The Lifecycle and Accountability working file is output-scoring rubric that never fails a high-risk output after a scorecard that rated 100% of outputs 'acceptable'. Content-attribution program lead in a firm whose vendor MSA is silent on training rights must name Policy or governance breach or Model defect for this AI Governance Layer file. Content-attribution program lead in a firm whose vendor MSA is silent on training rights has to name Policy or governance breach or Model defect for this AI Governance Layer Lifecycle and Accountability file.

DECISION Content-attribution program lead in a firm whose vendor MSA is silent on training rights must choose Policy or governance breach / Model defect / Dual failure / Hold for the missing fact using output-scoring rubric that never fails a high-risk output after a scorecard that rated 100% of outputs 'acceptable'.

HYPOTHESES TO TEST 1. The population in output-scoring rubric that never fails a high-risk output is the one a scorecard that rated 100% of outputs 'acceptable' named, so Policy or governance breach follows for this Lifecycle and Accountability file. 2. The population in output-scoring rubric that never fails a high-risk output is adjacent only to a scorecard that rated 100% of outputs 'acceptable'; Model defect is the honest AI Governance Layer call. 3. A firm whose vendor MSA is silent on training rights already contained a scorecard that rated 100% of outputs 'acceptable' before output-scoring rubric that never fails a high-risk output arrived; no new Lifecycle and Accountability path. 4. Provenance on output-scoring rubric that never fails a high-risk output after a scorecard that rated 100% of outputs 'acceptable' is broken; do not pick Policy or governance breach or Model defect yet.

ANALYSIS REQUIRED 1. Map the control-plane score in output-scoring rubric that never fails a high-risk output to the policy gate content-attribution program lead can enforce. 2. Name the override that would let deprecation will strand a proceed without a silent bypass. 3. Test whether a scorecard that rated 100% of outputs 'acceptable' changed routing, logging, or human-in-the-loop on the live agent path. 4. For this AI Governance Layer Lifecycle and Accountability file, read output-scoring rubric that never fails a high-risk output against a scorecard that rated 100% of outputs 'acceptable' and write the one fact that would move deprecation will strand a for content-attribution program lead.

RECOMMENDATION Choose Policy or governance breach / Model defect / Dual failure / Hold for the missing fact on this AI Governance Layer / Lifecycle and Accountability packet (output-scoring rubric that never fails a high-risk output after a scorecard that rated 100% of outputs 'acceptable'). The follow-on Lifecycle and Accountability action is what content-attribution program lead does next: implement the option, assign an owner, and log the missing fact.