Recoverable Identifier

arXiv:2605.08024 · detector doi_compliance · incontrovertible · 2026-05-19 11:18:37.489943+00:00

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Evidence text

In contrast, the frozen AI classifier exhibits a localized failure region where accuracy collapses. MPD 2-Router largely recovers this region, leaving residual errors sparse rather than spatially clustered. Its deferral mass is concentrated on the AI failure region and suppressed where the frozen classifier is already reliable. Thus, MPD2-Router does not spend expert capacity uniformly or merely to satisfy a budget; it makes selective, Pareto-favorable human–AI routing decisions by allocating expert review where the expected marginal clinical value is highest. Together, the matched-subset, operating-point, and spatial analyses support the central claim of MPD2-Router: glaucoma deferral is not a binary choice between AI and a homogeneous human fallback. It is an instance-wise, mask-aware allocation problem under heterogeneous reader behavior, asymmetric diagnostic harm, and localized model failure. MPD 2-Router improves over every individual expert on that expert’s own available cases precisely because it learns this structured human–AI complementarity. H Dataset details. Dataset access, licenses, and terms of use.We use only previously released ophthalmic datasets and credit the original creators in all cases. Raw fundus images and raw annotations are not redistributed with this submission. Instead, we provide preprocessing scripts, configuration files, split identifiers, and instructions for obtaining each dataset from its original source, so that users can 27 Figure 7: Spat

Evidence payload

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  "reconstructed_doi": "10.6084/m9.figshare.26049574.Color",
  "ref_index": 13,
  "resolved_title": null,
  "verdict_class": "incontrovertible"
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