Integrity report for CryoNet: A Deep Learning Framework for Multi-Modal Debris-Covered Glacier Mapping. A Case Study of the Poiqu Basin, Central Himalaya

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

arXiv:2605.21527 · pith:2026:S3POQUU6SSPDKWAIJIUQSTM3KV

0Critical

0Advisory

5Detectors run

2026-05-29Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

ai_meta_artifact completed v1.0.0 · findings 0 · 2026-05-29 00:37:10.693628+00:00

doi_title_agreement completed v1.0.0 · findings 0 · 2026-05-28 18:03:36.986922+00:00

doi_compliance completed v1.0.0 · findings 0 · 2026-05-26 02:15:41.434548+00:00

claim_evidence completed v1.0.0 · findings 0 · 2026-05-26 00:03:56.950729+00:00

cited_work_retraction completed v1.0.0 · findings 0 · 2026-05-22 00:52:24.092616+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/S3POQUU6/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.