Assess whether audits can reconstruct who authorized what from output-scoring

SITUATION The working file is output-scoring rubric that never fails a high-risk output after a customer discovering AI copy with no disclosure. Post-deployment monitoring owner in a manufacturer sunsetting a vision model still used in QA has to name Policy or governance breach or Model defect for this AI Governance Layer Control Plane and Scoring file.

DECISION Post-deployment monitoring owner in a manufacturer sunsetting a vision model still used in QA 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 customer discovering AI copy with no disclosure.

HYPOTHESES TO TEST 1. A customer discovering AI copy with no disclosure is noise around an already-controlled Control Plane and Scoring process in a manufacturer sunsetting a vision model still used in QA, given output-scoring rubric that never fails a high-risk output. 2. A customer discovering AI copy with no disclosure is the event in output-scoring rubric that never fails a high-risk output that forces Policy or governance breach for post-deployment monitoring owner under AI Governance Layer. 3. Output-scoring rubric that never fails a high-risk output shows a one-file miss after a customer discovering AI copy with no disclosure, not a Control Plane and Scoring program failure. 4. Output-scoring rubric that never fails a high-risk output cannot decide audits can reconstruct who yet after a customer discovering AI copy with no disclosure; hold is the only AI Governance Layer close a manufacturer sunsetting a vision model still used in QA can defend.

ANALYSIS REQUIRED 1. Score whether the agent action in output-scoring rubric that never fails a high-risk output was in-policy, out-of-policy, or unlogged. 2. Confirm the inventory line still matches the running configuration in a manufacturer sunsetting a vision model still used in QA. 3. Map the control-plane score in output-scoring rubric that never fails a high-risk output to the policy gate post-deployment monitoring owner can enforce. 4. For this AI Governance Layer Control Plane and Scoring file, read output-scoring rubric that never fails a high-risk output against a customer discovering AI copy with no disclosure and write the one fact that would move audits can reconstruct who for post-deployment monitoring owner.

RECOMMENDATION Choose Policy or governance breach / Model defect / Dual failure / Hold for the missing fact on this AI Governance Layer / Control Plane and Scoring packet (output-scoring rubric that never fails a high-risk output after a customer discovering AI copy with no disclosure). If output-scoring rubric that never fails a high-risk output cannot force a AI Governance Layer label under Control Plane and Scoring, stop. Do not invent missing evidence a manufacturer sunsetting a vision model still used in QA does not have.