Updated Method Guidelines for Cochrane Musculoskeletal Group Systematic Reviews and Metaanalyses
Bibliographic record
Abstract
The Cochrane Musculoskeletal Group (CMSG), one of 53 groups of the not-for-profit, international Cochrane Collaboration, prepares, maintains, and disseminates systematic reviews of treatments for musculoskeletal diseases. It is important that authors conducting CMSG reviews and the readers of our reviews be aware of and use updated, state-of-the-art systematic review methodology. One hundred sixty reviews have been published. Previous method guidelines for systematic reviews of interventions in the musculoskeletal field published in 2006 have been substantially updated to incorporate methodological advances that are mandatory or highly desirable in Cochrane reviews and knowledge translation advances. The methodological advances include new guidance on searching, new risk-of-bias assessment, grading the quality of the evidence, the new Summary of Findings table, and comparative effectiveness using network metaanalysis. Method guidelines specific to musculoskeletal disorders are provided by CMSG editors for various aspects of undertaking a systematic review. These method guidelines will help improve the quality of reporting and ensure high standards of conduct as well as consistency across CMSG reviews.
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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 | 0.145 | 0.462 |
| Meta-epidemiology (narrow) | 0.007 | 0.008 |
| Meta-epidemiology (broad) | 0.013 | 0.024 |
| Bibliometrics | 0.030 | 0.035 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.010 | 0.005 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.092 | 0.025 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".