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Integrity report for Leveraging Large Language Models to Improve Precision in Randomized Controlled Trials

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

arXiv:2605.30157 · pith:2026:4IUL6ECMP4XXNSNEV4FSRDCKVP

0Critical
0Advisory
6Detectors run
2026-06-05Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

ai_meta_artifact skipped v1.0.0 · findings 0 · 2026-06-05 03:35:50.160133+00:00
claim_evidence completed v1.0.0 · findings 0 · 2026-06-03 12:28:24.927902+00:00
external_links completed v1.0.0 · findings 0 · 2026-05-31 17:32:05.012114+00:00
citation_quote_validity skipped v0.1.0 · findings 0 · 2026-05-31 07:50:41.838956+00:00
shingle_duplication skipped v0.1.0 · findings 0 · 2026-05-29 17:50:04.021593+00:00
cited_work_retraction completed v1.0.0 · findings 0 · 2026-05-29 05:24:18.669963+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/4IUL6ECM/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.