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Record W4366386744 · doi:10.1136/bmjebm-2022-112111

Rapid reviews methods series: Guidance on assessing the certainty of evidence

2023· article· en· W4366386744 on OpenAlex
Gerald Gartlehner, Barbara Nußbaumer-Streit, Declan Devane, Leila C. Kahwati, Meera Viswanathan, Valerie King, Amir Qaseem, Elie A. Akl, Holger J Schuenemann

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBMJ evidence-based medicine · 2023
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsMcMaster UniversityImpact
FundersPublic Health Agency
KeywordsGrading (engineering)Systematic reviewComputer scienceRating systemCertaintyManagement scienceMedicineActuarial scienceMEDLINEEngineeringMathematicsBusinessPolitical science

Abstract

fetched live from OpenAlex

This paper is part of a series of methodological guidance from the Cochrane Rapid Reviews Methods Group. Rapid reviews (RRs) use modified systematic review methods to accelerate the review process while maintaining systematic, transparent and reproducible methods. This paper addresses considerations for rating the certainty of evidence (COE) in RRs. We recommend the full implementation of GRADE (Grading of Recommendations, Assessment, Development and Evaluation) for Cochrane RRs if time and resources allow.If time or other resources do not permit the full implementation of GRADE, the following recommendations can be considered: (1) limit rating COE to the main intervention and comparator and limit the number of outcomes to critical benefits and harms; (2) if a literature review or a Delphi approach to rate the importance of outcomes is not feasible, rely on informal judgements of knowledge users, topic experts or team members; (3) replace independent rating of the COE by two reviewers with single-reviewer rating and verification by a second reviewer and (4) if effect estimates of a well-conducted systematic review are incorporated into an RR, use existing COE grades from such a review. We advise against changing the definition of COE or the domains considered part of the GRADE approach for RRs.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Methods · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptMetaresearch
Domain: Methods · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
models agreeAgreement compares identical category sets and study designs across arms.

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)0.567
metaresearch head score (Gemma)0.701
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.385
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.5670.701
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0010.008
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0040.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.002

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 head0.955
GPT teacher head0.695
Teacher spread0.260 · 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