Assess whether disagreement should block, queue, or log (452480)

SITUATION A scorecard that rated 100% of outputs 'acceptable' put output-scoring rubric that never fails a high-risk output in front of multi-model reconciliation lead in a regulated entity that cannot reconstruct last month's decisions. This AI Governance Layer / Lifecycle and Accountability close is disagreement should block, queue, from output-scoring rubric that never fails a high-risk output, and the live options are Disagreement should block, queue,, Log.

DECISION Multi-model reconciliation lead in a regulated entity that cannot reconstruct last month's decisions must choose Disagreement should block, queue, / Log using output-scoring rubric that never fails a high-risk output after a scorecard that rated 100% of outputs 'acceptable'.

HYPOTHESES TO TEST 1. Output-scoring rubric that never fails a high-risk output reads as Disagreement should block, queue, once a scorecard that rated 100% of outputs 'acceptable' is lined up to the same AI Governance Layer population. 2. Output-scoring rubric that never fails a high-risk output is closer to Log after a scorecard that rated 100% of outputs 'acceptable'; Disagreement should block, queue, would over-claim this Lifecycle and Accountability extract. 3. A dual reading is still live in output-scoring rubric that never fails a high-risk output for multi-model reconciliation lead in a regulated entity that cannot reconstruct last month's decisions. 4. Output-scoring rubric that never fails a high-risk output is missing the fact multi-model reconciliation lead needs after a scorecard that rated 100% of outputs 'acceptable'; stop this AI Governance Layer close.

ANALYSIS REQUIRED 1. Test whether a scorecard that rated 100% of outputs 'acceptable' changed routing, logging, or human-in-the-loop on the live agent path. 2. Score whether the agent action in output-scoring rubric that never fails a high-risk output was in-policy, out-of-policy, or unlogged. 3. Confirm the inventory line still matches the running configuration in a regulated entity that cannot reconstruct last month's decisions. 4. For this AI Governance Layer Lifecycle and Accountability file, read output-scoring rubric that never fails a high-risk output against a scorecard that rated 100% of outputs 'acceptable' and write the one fact that would move disagreement should block, queue, for multi-model reconciliation lead.

RECOMMENDATION Choose Disagreement should block, queue, / Log on this AI Governance Layer / Lifecycle and Accountability packet (output-scoring rubric that never fails a high-risk output after a scorecard that rated 100% of outputs 'acceptable'). The follow-on Lifecycle and Accountability action is what multi-model reconciliation lead does next: implement the option, assign an owner, and log the missing fact.