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Integrity report for Dirichlet-Based Monte Carlo Dropout for Uncertainty Estimation in Neural Networks

A machine-verified record of the checks Pith has run against this paper: detector runs, findings, signed bundle events, and canonical identifiers.

arXiv:2605.23635 · pith:2026:ZK72IZVGRMCKKVIJJ4PZAZIBKU

0Critical
0Advisory
6Detectors run
2026-06-05Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

doi_compliance completed v1.0.0 · findings 0 · 2026-06-05 04:36:12.919816+00:00
doi_title_agreement completed v1.0.0 · findings 0 · 2026-06-05 03:36:07.415412+00:00
ai_meta_artifact completed v1.0.0 · findings 0 · 2026-06-01 03:40:21.160685+00:00
claim_evidence completed v1.0.0 · findings 0 · 2026-05-28 12:44:50.335579+00:00
citation_quote_validity completed v0.1.0 · findings 0 · 2026-05-25 09:50:46.776056+00:00
cited_work_retraction completed v1.0.0 · findings 0 · 2026-05-25 06:25:21.913103+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/ZK72IZVG/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.