A clinical prediction rule based on preoperative factors predicted the development of delirium after cardiac surgeryCommentary
Bibliographic record
Abstract
Can a clinical prediction rule based on preoperative factors accurately predict the development of delirium after cardiac surgery? ### Design: 2 cohort studies: 1 for derivation and 1 for validation of the prediction model. ### Setting: 2 academic centres and 1 Veterans Administration hospital (derivation set), and 1 academic medical centre and 1 Veterans Administration hospital (validation set). ### Patients: 122 patients (mean age 75 y, 80% men) for the derivation set and 109 patients (mean age 73 y, 73% men) for the validation set. Patients were planning to have cardiac surgery (coronary artery bypass graft [CABG], mitral or aortic valve replacement or repair, or combined CABG-valve). Exclusion criteria included residence >60 miles from study centre, medical …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".