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Conditional validity of quantum event classifiers under collider systematics and quantum estimation uncertainty
Claims about a deployed quantum machine-learning classifier can fail when target data shift or when finite-shot quantum evaluation randomizes the model itself. We develop an information-conditional, fail-closed auditing framework that returns supported, refuted or unresolved verdicts with anytime-va
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