Cochrane Airways Group reviews were prioritized for updating using a pragmatic approach
Bibliographic record
Abstract
OBJECTIVES: Cochrane Reviews should address the most important questions for guideline writers, clinicians, and the public. It is not possible to keep all reviews up-to-date, so the Cochrane Airways Group (CAG) decided to prioritize updates and new reviews without requesting additional resources. The aim of the objective was to develop pragmatic and transparent prioritization techniques to identify 25 to 35 high-priority updates from a total of 270 CAG Reviews and become more selective over which new reviews we publish. STUDY DESIGN AND SETTING: We used elements from existing prioritization processes, including existing health care uncertainties, expert opinion, and a decision tool. We did not conduct a full face-to-face workshop or an iterative group decision-making process. RESULTS: We prioritized 30 reviews in need of updating and aimed to update these within 2 years. Within the first 18 months, nine of these have been published. CONCLUSION: A pragmatic approach to prioritization can indicate priority reviews without an excessive drain on time and resources. The steps provide us with better control over the reviews in our scope and can be built on in the future.
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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 | 0.450 | 0.757 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.010 | 0.012 |
| Bibliometrics | 0.056 | 0.031 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.018 | 0.014 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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.
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".