Integrity report for Uncertainty-Aware Prediction of Lung Tumor Growth from Sparse Longitudinal CT Data via Bayesian Physics-Informed Neural Networks

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

arXiv:2605.13560 · pith:2026:JLQ4U25RUKXLEJA7DGCA2YKVX2

0Critical

0Advisory

4Detectors run

2026-05-21Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

doi_title_agreement completed v1.0.0 · findings 0 · 2026-05-21 13:31:42.505638+00:00

doi_compliance completed v1.0.0 · findings 0 · 2026-05-21 10:33:27.533634+00:00

claim_evidence completed v1.0.0 · findings 0 · 2026-05-20 23:02:16.157466+00:00

ai_meta_artifact completed v1.0.0 · findings 0 · 2026-05-19 08:35:50.686760+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/JLQ4U25R/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.