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Integrity report for SR-CGCNN: Shared Recurrent Convolution in Crystal Graph Neural Networks for Materials Property Prediction

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

arXiv:2605.01304 · pith:2026:VE4HWBM6DCP55BBHCK6LXZXVE5

0Critical
0Advisory
2Detectors run
2026-05-20Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

ai_meta_artifact completed v1.0.0 · findings 0 · 2026-05-20 18:35:31.881988+00:00
doi_compliance completed v1.0.0 · findings 0 · 2026-05-19 17:22:17.260570+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/VE4HWBM6DCP55BBHCK6LXZXVE5/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.