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Aligning fMRI analysis with movie narrative structure unlocks significant gains in ADHD classification accuracy, outperforming generic whole-run connectivity models.
Dynamic hypergraph fusion unlocks condition-specific neural reconfigurations, outperforming static connectomes for predicting cognitive function and classifying neurological disorders.
Post-hoc calibrators routinely and silently flip top-1 predictions without improving net accuracy, but a zero-parameter probability vector repair guarantees exact prediction invariance while paradoxically improving ECE, NLL, and Brier scores.