Assess whether procurement should fail a vendor lacking eval rights (60f85a)

SITUATION The working file is output-scoring rubric that never fails a high-risk output after two production models recommending opposite actions on the same file. Enterprise AI control-plane owner in a bank running three models on the same credit file has to name Policy or governance breach or Model defect for this AI Governance Layer Control Plane and Scoring file.

DECISION Enterprise AI control-plane owner 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 two production models recommending opposite actions on the same file.

HYPOTHESES TO TEST 1. Two production models recommending opposite actions on the same file is noise around an already-controlled Control Plane and Scoring process in a bank running three models on the same credit file, given output-scoring rubric that never fails a high-risk output. 2. Two production models recommending opposite actions on the same file is the event in output-scoring rubric that never fails a high-risk output that forces Policy or governance breach for enterprise AI control-plane owner under AI Governance Layer. 3. Output-scoring rubric that never fails a high-risk output shows a one-file miss after two production models recommending opposite actions on the same file, not a Control Plane and Scoring program failure. 4. Output-scoring rubric that never fails a high-risk output cannot decide procurement should fail a yet after two production models recommending opposite actions on the same file; hold is the only AI Governance Layer close a bank running three models on the same credit file can defend.

ANALYSIS REQUIRED 1. Name the override that would let procurement should fail a proceed without a silent bypass. 2. Test whether two production models recommending opposite actions on the same file 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 two production models recommending opposite actions on the same file and write the one fact that would move procurement should fail a for enterprise AI control-plane 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 two production models recommending opposite actions on the same file). The follow-on Control Plane and Scoring action is what enterprise AI control-plane owner does next: implement the option, assign an owner, and log the missing fact.