Integrity report for Machine-Learning-Enhanced Non-Invasive Testing for MASLD Fibrosis: Shallow-Deep Neural Networks Versus FIB-4, Tabular Foundation Models, and Large Language Models

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

arXiv:2605.20523 · pith:2026:3AVGJW4NJTWZ6YKHT5FFODF5IU

0Critical

0Advisory

5Detectors run

2026-05-24Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

doi_title_agreement completed v1.0.0 · findings 0 · 2026-05-24 07:32:27.798447+00:00

doi_compliance completed v1.0.0 · findings 0 · 2026-05-24 07:16:00.717372+00:00

claim_evidence completed v1.0.0 · findings 0 · 2026-05-24 05:03:19.266399+00:00

cited_work_retraction completed v1.0.0 · findings 0 · 2026-05-21 17:22:29.219773+00:00

ai_meta_artifact skipped v1.0.0 · findings 0 · 2026-05-21 02:33:38.737925+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/3AVGJW4N/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.