Bibliographic record
Abstract
Editor In a study of 12 296 patients from 76 countries1, the GlobalSurg Collaborative report lower 30-day perioperative mortality when the World Health Organization Surgical Safety Checklist is used. But, given that the authors have failed to account for institutional and patient/contextual factors associated with checklist use, are the conclusions drawn from this observational study realistic? Checklists are often adopted at an institutional level. Institutions that implement checklists may have a greater commitment to quality than those that do not, and this may be reflected in other measures of higher quality care (e.g. greater staffing and resources), and other factors that could affect patient outcomes. For jurisdictions where checklist adoption has not been widespread, differences between institutions that do and do not adopt the checklist may be particularly marked. If checklist use is an indicator of hospital quality, superior outcomes observed in the checklist group may have occurred irrespective of its use. Yet, the authors have not adjusted for institution-level factors or accounted for correlated outcomes within institutions.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.014 | 0.009 |
| Insufficient payload (model declined to judge) | 0.307 | 0.150 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".