Integrity report for SwAIther-Precip: Lead-Time-Aware Bias Correction Enables Kilometer-Scale Downscaling of Global AI Precipitation Forecasts over Switzerland

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

arXiv:2605.16163 · pith:2026:5HUPYUGZEQO62FBAJXDWXRIEF7

0Critical

0Advisory

6Detectors run

2026-05-20Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

doi_title_agreement completed v1.0.0 · findings 0 · 2026-05-20 18:01:26.524099+00:00

doi_compliance completed v1.0.0 · findings 0 · 2026-05-20 17:52:54.295958+00:00

claim_evidence completed v1.0.0 · findings 0 · 2026-05-20 16:42:07.364460+00:00

cited_work_retraction completed v1.0.0 · findings 0 · 2026-05-19 18:22:01.587226+00:00

ai_meta_artifact skipped v1.0.0 · findings 0 · 2026-05-19 17:33:31.035588+00:00

external_links completed v1.0.0 · findings 0 · 2026-05-19 17:31:47.409231+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/5HUPYUGZ/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.