[The BMJ Rapid Recommendations: towards a new model for the production of clinical practice guidelines].
Bibliographic record
Abstract
Guidelines play a central role in clinical practice, but their development often does not meet trustworthiness standards, which makes them vulnerable to conflict of interest. Additional problems -include their insufficient updating, and current formats that do not support shared decision-making. To address these issues, we have created the Rapid Recommendations, in collaboration with the British -Medical Journal. In this innovative approach, we a) identify new practice-changing evidence ; b) incorporate them in updated -systematics reviews in about 45 days ; c) gather an international and unconflicted panel including patients and d) publish trust-worthy recommendation in about 90 days, along with new multilayered evidence summaries and tools that facilitate shared decision-making.
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 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 | 0.211 | 0.598 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.021 | 0.019 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.020 | 0.016 |
| Open science | 0.010 | 0.019 |
| Research integrity | 0.025 | 0.026 |
| Insufficient payload (model declined to judge) | 0.039 | 0.047 |
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".