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Record W2090768368 · doi:10.1371/journal.pone.0030683

Endorsement of the CONSORT Statement by High-Impact Medical Journals in China: A Survey of Instructions for Authors and Published Papers

2012· article· en· W2090768368 on OpenAlexaff
Xiaoqian Li, Kunming Tao, Qing-Hui Zhou, David Moher, Hongyun Chen, Fu-zhe Wang, Changquan Ling

Bibliographic record

VenuePLoS ONE · 2012
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsOttawa Hospital
FundersE-Institutes of Shanghai Municipal Education CommissionShanghai University of Traditional Chinese MedicineShanghai Municipal Education Commission
KeywordsConsolidated Standards of Reporting TrialsMedical journalClinical trialRandomized controlled trialMedicinePublishingGuidelineMEDLINEAlternative medicineCitationFamily medicineStatement (logic)PublicationBibliometricsMedical educationLibrary scienceComputer sciencePolitical scienceSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: The CONSORT Statement is a reporting guideline for authors when reporting randomized controlled trials (RCTs). It offers a standard way for authors to prepare RCT reports. It has been endorsed by many high-impact medical journals and by international editorial groups. This study was conducted to assess the endorsement of the CONSORT Statement by high-impact medical journals in China by reviewing their instructions for authors. METHODOLOGY/PRINCIPAL FINDINGS: A total of 200 medical journals were selected according to the Chinese Science and Technology Journal Citation Reports, 195 of which publish clinical research papers. Their instructions for authors were reviewed and all texts mentioning the CONSORT Statement or CONSORT extension papers were extracted. Any mention of the Uniform Requirements for Manuscripts Submitted to Biomedical Journals (URM) developed by the International Committee of Medical Journal Editors (ICMJE) or 'clinical trial registration' was also extracted. For journals endorsing the CONSORT Statement, their most recently published RCT reports were retrieved and evaluated to assess whether the journals have followed what the CONSORT Statement required. Out of the 195 medical journals publishing clinical research papers, only six (6/195, 3.08%) mentioned 'CONSORT' in their instructions for authors; out of the 200 medical journals surveyed, only 14 (14/200, 7.00%) mentioned 'ICMJE' or 'URM' in their instructions for authors, and another five journals stated in their instructions for authors that clinical trials should have trial registration numbers and that priority would be given to clinical trials which had been registered. Among the 62 RCT reports published in the six journals endorsing the CONSORT Statement, 20 (20/62, 32.26%) contained flow diagrams and only three (3/62, 4.84%) provided trial registration information. CONCLUSIONS/SIGNIFICANCE: Medical journals in China endorsing either the CONSORT Statement or the ICMJE's URM constituted a small percentage of the total; all of these journals used ambiguous language regarding what was expected of authors.

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)0.151
metaresearch head score (Gemma)0.479
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.987
Threshold uncertainty score0.798

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1510.479
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0130.015
Science and technology studies0.0030.003
Scholarly communication0.0060.005
Open science0.0030.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.658
GPT teacher head0.496
Teacher spread0.162 · 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 designObservational
DomainReporting
GenreEmpirical

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

Citations33
Published2012
Admission routes1
Has abstractyes

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