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#artificial intelligence Preprint Aug 2026

Spending Scarce Confirmatory PET Measurements: Target-Aligned Validation in A4/LEARN

This paper applies the A4/LEARN PET archive, treating observed PET as a design laboratory for scarce-confirmation studies and asks a deliberately operational question: when is simple transparent PET validation enough, and when is a fitted residual-uncertainty score worth the added complexity?

E. Cui, Qiang Yang, M. Zhang · 0 citations

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