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Record W2126122920 · doi:10.3899/jrheum.121306

Updated Method Guidelines for Cochrane Musculoskeletal Group Systematic Reviews and Metaanalyses

2013· article· en· W2126122920 on OpenAlexafffundvenue
Elizabeth Ghogomu, Lara Maxwell, Rachelle Buchbinder, Tamara Rader, Jordi Pardo Pardo, Renea V Johnston, Robin Christensen, Anne WS Rutjes, Tania Winzenberg, Jasvinder A. Singh, Gustavo Zanoli, George A. Wells, Peter Tugwell

Bibliographic record

VenueThe Journal of Rheumatology · 2013
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsCochraneInstitute of Population and Public HealthUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsSystematic reviewMedicineGrading (engineering)MEDLINEPsychological interventionQuality of evidenceMeta-analysisPhysical therapyPathologyPsychiatryEngineering

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.263
metaresearch head score (Gemma)0.172
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.603
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2630.172
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0090.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
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 head0.634
GPT teacher head0.572
Teacher spread0.062 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
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

Citations149
Published2013
Admission routes3
Has abstractyes

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