Assess whether a split between models is a review queue or noise (39ff79)

Situation

A bank running three models on the same credit file cannot treat a scorecard that rated 100% of outputs 'acceptable' as color commentary on vendor MSA clauses on training, indemnity, and subprocessors. Content-attribution program lead must close a split between models from that extract under AI Governance Layer / Audit and Vendor Terms.

Decision

Content-attribution program lead in a bank running three models on the same credit file must choose A split between models is a review queue / Noise using vendor MSA clauses on training, indemnity, and subprocessors after a scorecard that rated 100% of outputs 'acceptable'.

Hypotheses to test

• Authorize A split between models is a review queue now; vendor MSA clauses on training, indemnity, and subprocessors already has the discriminator after a scorecard that rated 100% of outputs 'acceptable'.
• Keep Noise in force until vendor MSA clauses on training, indemnity, and subprocessors is completed after a scorecard that rated 100% of outputs 'acceptable' for content-attribution program lead.
• Treat vendor MSA clauses on training, indemnity, and subprocessors as A split between models is a review queue because both readings appear after a scorecard that rated 100% of outputs 'acceptable'.
• Refuse a AI Governance Layer close: content-attribution program lead does not have the page a split between models turns on in vendor MSA clauses on training, indemnity, and subprocessors.

Analysis required

• Map the control-plane score in vendor MSA clauses on training, indemnity, and subprocessors to the policy gate content-attribution program lead can enforce.
• Name the override that would let a split between models proceed without a silent bypass.
• Test whether a scorecard that rated 100% of outputs 'acceptable' changed routing, logging, or human-in-the-loop on the live agent path.
• For this AI Governance Layer Audit and Vendor Terms file, read vendor MSA clauses on training, indemnity, and subprocessors against a scorecard that rated 100% of outputs 'acceptable' and write the one fact that would move a split between models for content-attribution program lead.

Recommendation

Choose A split between models is a review queue / Noise on this AI Governance Layer / Audit and Vendor Terms packet (vendor MSA clauses on training, indemnity, and subprocessors after a scorecard that rated 100% of outputs 'acceptable'). Lead with the AI Governance Layer option vendor MSA clauses on training, indemnity, and subprocessors can support after a scorecard that rated 100% of outputs 'acceptable', then the two facts that force it, then the Monday action for content-attribution program lead in a bank running three models on the same credit file.