Integrity report for Accurate, Efficient, and Explainable Deep Learning Approaches for Environmental Science Problems

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

arXiv:2605.19366 · pith:2026:PCVRGVLTDENRIKEMLPALI276C7

0Critical

0Advisory

6Detectors run

2026-05-25Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

doi_title_agreement completed v1.0.0 · findings 0 · 2026-05-25 10:32:44.097249+00:00

claim_evidence completed v1.0.0 · findings 0 · 2026-05-25 10:23:47.256428+00:00

doi_compliance completed v1.0.0 · findings 0 · 2026-05-25 09:04:17.107667+00:00

citation_quote_validity completed v0.1.0 · findings 0 · 2026-05-20 21:49:54.766927+00:00

cited_work_retraction completed v1.0.0 · findings 0 · 2026-05-20 14:52:04.154726+00:00

ai_meta_artifact skipped v1.0.0 · findings 0 · 2026-05-20 02:33:29.707308+00:00

Findings

No public integrity findings for this paper.

Signed record

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