An automated approach to improve clinical trial registration and to identify outcome changes on ClinicalTrials.gov
Evaluates an LLM-assisted method for detecting incomplete outcome definitions and outcome changes on ClinicalTrials.gov.
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- Shared materials: Prompts
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- Model outputs: Live public OSF file inventory contains: Model output.zip. This verifies shared model outputs, not access to every original input or executable analysis script.
- Prompts: Live public OSF file inventory contains: Prompts for assessing outcome definition completeness and detecting outcome changes_Nov142025.docx.
- Registration: OSF API identifies this as a public registration, registered None; not merely an editable project. Open-Ended Registration schema, registered_from 2tyh3; nonwithdrawn. OpenAlex had incorrectly classified this as a research project.
- Earlier preprint: Saved catalogue version matching based on title, ordered byline, and study content; prior manuscript DOI retained.
- Free full text: OpenAlex marks this location open access (gold); availability is metadata-reported, not an independently tested reusable license.
Publication details
Research themes
Research toolsReporting transparency
Author affiliations & identifiers
- Xiangji Ying: Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, NC, USA
- Kiran Ninan: Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, NC, USA · ORCID https://orcid.org/0000-0002-8085-6751
- Jean-Pierre Oberste: Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, NC, USA
- Colby J. Vorland: Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, IN, USA
- Tianjing Li: Department of Ophthalmology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Andrew W. Brown: Arkansas Children’s Research Institute, Little Rock, AR, USA; Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, AR, USA
- Joe D. Menke: School of Information Sciences, University of Illinois at Urbana-Champaign, Champaign, IL, USA
- Riaz Qureshi: Department of Ophthalmology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Nicholas J. DeVito: Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
- Matthew J. Page: Methods in Evidence Synthesis Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- Joanne E. McKenzie: Methods in Evidence Synthesis Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- Ian J. Saldanha: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Sirui Zhang: Department of Epidemiology, School of Public Health, Brown University, Providence, RI, USA
- Nancy J. Butcher: Child Health Evaluative Sciences, The Hospital for Sick Children Research Institute, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Martin Offringa: Child Health Evaluative Sciences, The Hospital for Sick Children Research Institute, Toronto, ON, Canada
- Jamie Cummins: Department for the Psychology of Digitalisation, University of Bern, Bern, Switzerland; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
- Halil Kilicoglu: School of Information Sciences, University of Illinois at Urbana-Champaign, Champaign, IL, USA
- Evan Mayo-Wilson: Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, NC, USA
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