# Originality, duplicate and claim boundary

## Distinct scope

This article governs what happens after a person changes an AI recommendation: the operating disposition, dispute reason, verified label, evaluation eligibility and training eligibility remain separate. It does not duplicate prior work on portfolio calibration, runtime identity, command arbitration, pre-execution authority, retrieval receipts, dead-letter recovery or AI-output re-entry.

The closest prior package, `A High Score Is Not a Shared Standard`, addresses whether a score and threshold transfer across facilities. This package addresses whether a human override is valid feedback for a defined label and dataset. The distinction is preserved in the title, examples, architecture and tool.

## Rights and exclusivity

This is a new Jared-authored owned article package. No external publisher has received this exact manuscript, tool or image package. No known exclusivity, assignment or rights transfer covers the exact work. The single assigned destination is Jared's personal authority site; do not cross-submit the manuscript.

## Claims

- The label-dispute layer is an authored operating method, not an adopted industry standard.
- All facilities, people, identifiers, model names, providers, evidence, times, labels, datasets and outcomes in the examples are fictional.
- No customer, deployment, product availability, adoption, certification, revenue, occupancy, performance, award or recognition claim is made.
- NIST and W3C sources support only the attributed general principles and do not validate this method.
- An operating override is not characterized as inherently right or wrong; the method preserves its authority, evidence and purpose.
- Evaluation eligibility and training eligibility are decisions, not inferred outcomes.
- The image is editorial and non-documentary.