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Record W4409483503 · doi:10.1136/bmj-2024-081124

CONSORT 2025 explanation and elaboration: updated guideline for reporting randomised trials

2025· article· en· W4409483503 on OpenAlexaff
Sally Hopewell, An‐Wen Chan, Gary S. Collins, Asbjørn Hróbjartsson, David Moher, Kenneth F. Schulz, R. Tunn, Rakesh Aggarwal, Michael Berkwits, Jesse A. Berlin, Nita Bhandari, Nancy J. Butcher, Marion Campbell, Runcie C.W. Chidebe, Diana Elbourne, Andrew Farmer, Dean Fergusson, Robert M. Golub, Steven N. Goodman, Tammy Hoffmann, John P. A. Ioannidis, Brennan C Kahan, Rachel L Knowles, Sarah E Lamb, Steff Lewis, Elizabeth Loder, Martin Offringa, Philippe Ravaud, Dawn P. Richards, Frank W. Rockhold, David L. Schriger, Nandi Siegfried, Sophie Staniszewska, R. Taylor, Lehana Thabane, David Torgerson, Sunita Vohra, Ian R. White, Isabelle Boutron

Bibliographic record

VenueBMJ · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsImpactUniversity of AlbertaRobarts Clinical TrialsSt. Joseph’s Healthcare HamiltonHospital for Sick ChildrenOttawa HospitalMcMaster UniversityWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsElaborationConsolidated Standards of Reporting TrialsGuidelineComputer scienceMedicineAlternative medicinePathology

Abstract

fetched live from OpenAlex

This is comment on: Hopewell S, et al. CONSORT 2025 explanation and elaboration: updated guideline for reporting randomised trials. BMJ. 2025 Apr 14;389:e081124. https://pubmed.ncbi.nlm.nih.gov/40228832 The CONSORT (2025) statement [1] writes about blinding as follows: “Unblinded outcome assessors may differentially assess subjective outcomes, and unblinded data analysts may introduce bias through the choice of analytical strategies, such as the selection of favourable time points or outcomes and by decisions to remove patients from the analyses. These biases have been well documented,” p.27 in [1]. One of the references to this statement, ref. no. 328, is to the trial by Karlowski, Chalmers et al. (1975) [2]. In the randomized, double-blind, placebo-controlled trial, Thomas Karlowski, Thomas Chalmers et al. observed that 6 g/day vitamin C significantly shortened the duration of colds, yet they concluded “that the effects demonstrated might be explained equally well by a break in the double blind.” The Karlowski (1975) trial has been widely used as evidence for the existence of the placebo effect, and also as evidence that the observed effects of vitamin C on the common cold are explained by the placebo effect [3]. However, it was shown already in 1996 that the placebo-effect interpretation of Karlowski, Chalmers, et al. was not valid [4-6].

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)0.185
metaresearch head score (Gemma)0.548
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.815
Threshold uncertainty score0.978

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1850.548
Meta-epidemiology (narrow)0.0050.006
Meta-epidemiology (broad)0.0100.015
Bibliometrics0.0200.017
Science and technology studies0.0020.006
Scholarly communication0.0110.008
Open science0.0110.007
Research integrity0.0210.026
Insufficient payload (model declined to judge)0.1250.086

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 head0.297
GPT teacher head0.582
Teacher spread0.285 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
DomainReporting
GenreMethods

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

Citations145
Published2025
Admission routes1
Has abstractyes

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Same venueBMJSame topicDelphi Technique in ResearchFrench-language works237,207