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Record W2754565696 · doi:10.1136/bmjopen-2017-017462

A protocol of a cross-sectional study evaluating an online tool for early career peer reviewers assessing reports of randomised controlled trials

2017· article· en· W2754565696 on OpenAlexaff
Anthony Chauvin, David Moher, Doug Altman, David L. Schriger, Sabina Alam, Sally Hopewell, Daniel Shanahan, Alessandro Recchioni, Philippe Ravaud, Isabelle Boutron

Bibliographic record

VenueBMJ Open · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersCancer Research UK
KeywordsMedicineProtocol (science)Psychological interventionPeer reviewMedical educationRandomized controlled trialSystematic reviewMEDLINEAlternative medicineFamily medicineNursingPathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Systematic reviews evaluating the impact of interventions to improve the quality of peer review for biomedical publications highlighted that interventions were limited and have little impact. This study aims to compare the accuracy of early career peer reviewers who use an innovative online tool to the usual peer reviewer process in evaluating the completeness of reporting and switched primary outcomes in completed reports. METHODS AND ANALYSIS: and indexed with the publication type 'Randomised Controlled Trial'. First, we will develop an online tool and training module based (a) on the Consolidated Standards of Reporting Trials (CONSORT) 2010 checklist and the Explanation and Elaboration document that would be dedicated to junior peer reviewers for assessing the completeness of reporting of key items and (b) the Centre for Evidence-Based Medicine Outcome Monitoring Project process used to identify switched outcomes in completed reports of the primary results of RCTs when initially submitted. Then, we will compare the performance of early career peer reviewers who use the online tool to the usual peer review process in identifying inadequate reporting and switched outcomes in completed reports of RCTs at initial journal submission. The primary outcome will be the mean number of items accurately classified per manuscript. The secondary outcomes will be the mean number of items accurately classified per manuscript for the CONSORT items and the sensitivity, specificity and likelihood ratio to detect the item as adequately reported and to identify a switch in outcomes. We aim to include 120 RCTs and 120 early career peer reviewers. ETHICS AND DISSEMINATION: The research protocol was approved by the ethics committee of the INSERM Institutional Review Board (21 January 2016). The study is based on voluntary participation and informed written consent. TRIAL REGISTRATION NUMBER: NCT03119376.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.284
metaresearch head score (Gemma)0.354
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.716
Threshold uncertainty score0.883

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2840.354
Meta-epidemiology (narrow)0.0040.005
Meta-epidemiology (broad)0.0070.006
Bibliometrics0.0110.009
Science and technology studies0.0060.006
Scholarly communication0.0060.007
Open science0.0050.004
Research integrity0.0080.011
Insufficient payload (model declined to judge)0.0840.032

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.952
GPT teacher head0.741
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designObservational
DomainEvaluation
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2017
Admission routes1
Has abstractyes

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