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Integrity report for Machine Learning Approaches to Point Defects in Non-Metallic Materials: A Review of Methods

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

arXiv:2605.16611 · pith:2026:SJPWZCVT45YJLVXXJBWON3XQ2D

0Critical
0Advisory
5Detectors run
2026-05-26Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

ai_meta_artifact completed v1.0.0 · findings 0 · 2026-05-26 18:43:57.337219+00:00
doi_title_agreement completed v1.0.0 · findings 0 · 2026-05-25 18:32:48.717603+00:00
doi_compliance completed v1.0.0 · findings 0 · 2026-05-24 16:52:56.864286+00:00
cited_work_retraction completed v1.0.0 · findings 0 · 2026-05-23 23:53:49.458035+00:00
claim_evidence completed v1.0.0 · findings 0 · 2026-05-21 19:42:33.773188+00:00

Findings

No public integrity findings for this paper.

Signed record

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