Method guidelines for Cochrane Musculoskeletal Group systematic reviews.
Bibliographic record
Abstract
The Cochrane Musculoskeletal Group (CMSG), one of 50 groups of the not-for-profit international Cochrane Collaboration, prepares, maintains, and disseminates systematic reviews of treatments for musculoskeletal diseases. To enhance the quality and usability of systematic reviews, the CMSG has developed tailored methodological guidelines for authors of CMSG systematic reviews. Recommendations specific to musculoskeletal disorders are provided for various aspects of undertaking a systematic review, including literature searching, inclusion criteria, quality assessment, grading of evidence, data collection, and data analysis. These guidelines will help researchers design, conduct, and report results of systematic reviews of trials in the following fields of musculoskeletal health: gout, osteoarthritis, osteoporosis, pediatric rheumatology, rheumatoid arthritis, soft tissue rheumatism, spondyloarthropathy, systemic lupus erythematosus, systemic sclerosis, and vasculitis. Systematic reviews need to be conducted according to high methodological standards. These recommendations on developing and performing a systematic review will help improve consistency among 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 | 0.126 | 0.291 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.014 | 0.015 |
| Bibliometrics | 0.045 | 0.042 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.009 | 0.006 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.141 | 0.035 |
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".