Assess whether a split between models is a review queue or noise (9c07c1)

Situation

Drift in a protected class the dashboard does not show put output-scoring rubric that never fails a high-risk output in front of decision-audit designer in a company whose agents can send email without a gate. This AI Governance Layer / Lifecycle and Accountability 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

Decision-audit designer in a company whose agents can send email without a gate must choose A split between models is a review queue / Noise using output-scoring rubric that never fails a high-risk output after drift in a protected class the dashboard does not show.

Hypotheses to test

• Drift in a protected class the dashboard does not show is noise around an already-controlled Lifecycle and Accountability process in a company whose agents can send email without a gate, given output-scoring rubric that never fails a high-risk output.
• Drift in a protected class the dashboard does not show is the event in output-scoring rubric that never fails a high-risk output that forces A split between models is a review queue for decision-audit designer under AI Governance Layer.
• Output-scoring rubric that never fails a high-risk output shows a one-file miss after drift in a protected class the dashboard does not show, not a Lifecycle and Accountability program failure.
• Output-scoring rubric that never fails a high-risk output cannot decide a split between models yet after drift in a protected class the dashboard does not show; hold is the only AI Governance Layer close a company whose agents can send email without a gate can defend.

Analysis required

• Score whether the agent action in output-scoring rubric that never fails a high-risk output was in-policy, out-of-policy, or unlogged.
• Confirm the inventory line still matches the running configuration in a company whose agents can send email without a gate.
• Map the control-plane score in output-scoring rubric that never fails a high-risk output to the policy gate decision-audit designer can enforce.
• For this AI Governance Layer Lifecycle and Accountability file, read output-scoring rubric that never fails a high-risk output against drift in a protected class the dashboard does not show and write the one fact that would move a split between models for decision-audit designer.