A catalogue of reporting guidelines for health research
Bibliographic record
Abstract
Growing evidence demonstrates widespread deficiencies in the reporting of health research studies. The EQUATOR Network is an international initiative that aims to enhance the reliability and value of the published health research literature. EQUATOR provides resources, education and training to facilitate good research reporting and assists in the development, dissemination and implementation of robust reporting guidelines. This paper presents a collection of tools and guidelines available on the EQUATOR website (http://www.equator-network.org) that have been developed to increase the accuracy and transparency of health research reporting.
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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 | 0.197 | 0.479 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.047 | 0.058 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.012 | 0.008 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.064 | 0.071 |
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".