Assess whether a split between models is a review queue or noise (c05d59)

Situation

An examiner asking who authorized last Tuesday's model output put output-scoring rubric that never fails a high-risk output in front of enterprise AI control-plane owner in a bank running three models on the same credit file. This AI Governance Layer / Control Plane and Scoring close is a split between models from output-scoring rubric that never fails a high-risk output, and the live options are A split between models is a review queue, Noise.

Decision

Enterprise AI control-plane owner in a bank running three models on the same credit file must choose A split between models is a review queue / Noise using output-scoring rubric that never fails a high-risk output after an examiner asking who authorized last Tuesday's model output.

Hypotheses to test

• Output-scoring rubric that never fails a high-risk output reads as A split between models is a review queue once an examiner asking who authorized last Tuesday's model output is lined up to the same AI Governance Layer population.
• Output-scoring rubric that never fails a high-risk output is closer to Noise after an examiner asking who authorized last Tuesday's model output; A split between models is a review queue would over-claim this Control Plane and Scoring extract.
• A dual reading is still live in output-scoring rubric that never fails a high-risk output for enterprise AI control-plane owner in a bank running three models on the same credit file.
• Output-scoring rubric that never fails a high-risk output is missing the fact enterprise AI control-plane owner needs after an examiner asking who authorized last Tuesday's model output; stop this AI Governance Layer close.

Analysis required

• Map the control-plane score in output-scoring rubric that never fails a high-risk output to the policy gate enterprise AI control-plane owner can enforce.
• Name the override that would let a split between models proceed without a silent bypass.
• Test whether an examiner asking who authorized last Tuesday's model output changed routing, logging, or human-in-the-loop on the live agent path.
• For this AI Governance Layer Control Plane and Scoring file, read output-scoring rubric that never fails a high-risk output against an examiner asking who authorized last Tuesday's model output and write the one fact that would move a split between models for enterprise AI control-plane owner.