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Integrity report for Quantized Machine Learning Models for Medical Imaging in Low-Resource Healthcare Settings

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

arXiv:2605.19207 · pith:2026:SKXLSB7TMDUUWYVP74XYSH45FC

0Critical
0Advisory
5Detectors run
2026-05-27Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

ai_meta_artifact completed v1.0.0 · findings 0 · 2026-05-27 05:38:04.974354+00:00
doi_title_agreement completed v1.0.0 · findings 0 · 2026-05-26 17:03:01.386462+00:00
claim_evidence completed v1.0.0 · findings 0 · 2026-05-25 11:03:47.793138+00:00
doi_compliance completed v1.0.0 · findings 0 · 2026-05-25 08:55:16.932159+00:00
cited_work_retraction completed v1.0.0 · findings 0 · 2026-05-20 17:22:14.987912+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/SKXLSB7T/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.