International multistakeholder consensus statement on post‐publication integrity issues in randomized clinical trials by Cairo Consensus Group
Bibliographic record
Abstract
The number of retractions of randomized clinical trials (RCTs) following post-publication allegations of misconduct is increasing. To address this issue, we aimed to establish an international multistakeholder consensus on post-publication integrity concerns related to RCTs. After prospective registration (https://osf.io/njksm), we assembled a multidisciplinary stakeholder group comprising 48 participants from 18 countries across six continents, recruited using a curated list of journal editors and snowballing. An underpinning evidence synthesis collated 89 articles related to post-publication integrity concerns. Integrity statements related to RCTs created were subjected to anonymized two-round Delphi survey. A hybrid face-to-face-online consensus development meeting was convened to consolidate the consensus. The response rates of the two Delphi survey rounds were 65% (31/48) and 67% (32/ 48), respectively. There were 101 and 41 statements in the first and second Delphi rounds, respectively. After the two Delphi rounds and the consensus development meeting, consensus was achieved on 104 statements consolidated to 84 after merging, editing, and removing duplicates. This set of statements included general aspects (n = 9), journal instructions (n = 14), editorial and peer review (n = 7), correspondence and complaints (n = 4), investigations for integrity concerns (n = 16), decisions and sanctions (n = 9), critical appraisal guidance (n = 1), systematic reviews of RCTs (n = 8), and research recommendations (n = 16). In conclusion, this international multistakeholder consensus statement aimed to underpin policies for preventing post-publication integrity concerns in RCT publications and assist in improving investigations of misconduct allegations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.590 | 0.602 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.015 | 0.009 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.016 | 0.010 |
| Open science | 0.012 | 0.021 |
| Research integrity | 0.017 | 0.021 |
| Insufficient payload (model declined to judge) | 0.011 | 0.007 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".