Assess whether deprecation will strand a downstream process (73833a)
August 31, 2026
SITUATION In a hospital committee that never records dissent, output-scoring rubric that never fails a high-risk output is the evidence after a human reviewer who clicked approve in under two seconds. Model-deprecation manager has to pick Policy or governance breach or Model defect for this AI Governance Layer Control Plane and Scoring close using output-scoring rubric that never fails a high-risk output.
DECISION Model-deprecation manager in a hospital committee that never records dissent 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 human reviewer who clicked approve in under two seconds.
HYPOTHESES TO TEST 1. A human reviewer who clicked approve in under two seconds is noise around an already-controlled Control Plane and Scoring process in a hospital committee that never records dissent, given output-scoring rubric that never fails a high-risk output. 2. A human reviewer who clicked approve in under two seconds is the event in output-scoring rubric that never fails a high-risk output that forces Policy or governance breach for model-deprecation manager under AI Governance Layer. 3. Output-scoring rubric that never fails a high-risk output shows a one-file miss after a human reviewer who clicked approve in under two seconds, not a Control Plane and Scoring program failure. 4. Output-scoring rubric that never fails a high-risk output cannot decide deprecation will strand a yet after a human reviewer who clicked approve in under two seconds; hold is the only AI Governance Layer close a hospital committee that never records dissent can defend.
ANALYSIS REQUIRED 1. Name the override that would let deprecation will strand a proceed without a silent bypass. 2. Test whether a human reviewer who clicked approve in under two seconds changed routing, logging, or human-in-the-loop on the live agent path. 3. Score whether the agent action in output-scoring rubric that never fails a high-risk output was in-policy, out-of-policy, or unlogged. 4. For this AI Governance Layer Control Plane and Scoring file, read output-scoring rubric that never fails a high-risk output against a human reviewer who clicked approve in under two seconds and write the one fact that would move deprecation will strand a for model-deprecation manager.
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 human reviewer who clicked approve in under two seconds). The follow-on Control Plane and Scoring action is what model-deprecation manager does next: implement the option, assign an owner, and log the missing fact.
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