This public comment proposes five targeted additions to the NIST AI 200-2 initial public draft, The TEVV-Athlon Framework for Evaluating AI Systems. The recommendations address how a TEVV-Athlon should report results when an instrument fails, coverage is incomplete, the observed subject differs from the intended subject, or later evidence changes what can be concluded. The proposed additions focus on preserving UNKNOWN findings and PARTIAL coverage, making evaluator execution and failure modes observable, preserving provenance and claim-specific source authority, separating generation, criticism, observation, and acceptance roles, and using discriminating controls with postcondition verification. The recommendations retain the framework’s four-stage structure and the distinction between Measure and Manage, while proposing a run-level reporting discipline that makes the evidence supporting a conclusion, and the limits on that evidence, explicit at the Event, Tool, and Block levels.
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Gennaro Maida (2026) studied this question.
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