Assess whether procurement should fail a vendor lacking eval rights (3834ff)

SITUATION Output-scoring rubric that never fails a high-risk output arrived with a split so frequent that the queue is being auto-cleared for model-deprecation manager. That is a AI Governance Layer Lifecycle and Accountability decision on procurement should fail a in a bank running three models on the same credit file.

DECISION Model-deprecation manager in a bank running three models on the same credit file 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 split so frequent that the queue is being auto-cleared.

HYPOTHESES TO TEST 1. Model-deprecation manager can defend Policy or governance breach from output-scoring rubric that never fails a high-risk output after a split so frequent that the queue is being auto-cleared in a AI Governance Layer challenge. 2. Model-deprecation manager cannot defend Policy or governance breach from output-scoring rubric that never fails a high-risk output; Model defect is what the extract actually supports after a split so frequent that the queue is being auto-cleared. 3. A split so frequent that the queue is being auto-cleared never reached the population in output-scoring rubric that never fails a high-risk output — reopen intake, do not close procurement should fail a. 4. Two facts in output-scoring rubric that never fails a high-risk output after a split so frequent that the queue is being auto-cleared conflict for model-deprecation manager; hold this Lifecycle and Accountability file.

ANALYSIS REQUIRED 1. Map the control-plane score in output-scoring rubric that never fails a high-risk output to the policy gate model-deprecation manager can enforce. 2. Name the override that would let procurement should fail a proceed without a silent bypass. 3. Test whether a split so frequent that the queue is being auto-cleared 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 split so frequent that the queue is being auto-cleared and write the one fact that would move procurement should fail 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 / Lifecycle and Accountability packet (output-scoring rubric that never fails a high-risk output after a split so frequent that the queue is being auto-cleared). Lead with the AI Governance Layer option output-scoring rubric that never fails a high-risk output can support after a split so frequent that the queue is being auto-cleared, then the two facts that force it, then the Monday action for model-deprecation manager in a bank running three models on the same credit file.