Rapid reviews methods series: Guidance on assessing the certainty of evidence
Bibliographic record
Abstract
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.
How this classification was reachedexpand
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 arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Methods · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | Metaresearch Domain: Methods · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
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 | 0.389 | 0.720 |
| Meta-epidemiology (narrow) | 0.006 | 0.009 |
| Meta-epidemiology (broad) | 0.013 | 0.021 |
| Bibliometrics | 0.028 | 0.023 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.012 | 0.012 |
| Research integrity | 0.013 | 0.016 |
| Insufficient payload (model declined to judge) | 0.118 | 0.086 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".