Bibliographic record
Abstract
The Christmas issue contains three people's description of their ideal medical school. Read the descriptions: View the results of the voting Tell us why you voted the way you did Read what others have had to say We asked three people with an interest in education to speculate on what a medical school of the future might look like. Here Ed Peile and colleagues describe their Renaissance School; then Jeremy Anderson (p 1456) and Cindy Lam (p 1458) outline their visions. The Renaissance School will produce broadly educated doctors who think in terms of patients rather than organs and are strong, multiprofessional team players. The irresistible swing towards medical specialisation has brought advantages for patients, but arguably it has gone too far.1 As Horder puts it, “people are whole units who go wrong as a whole, and do not take kindly to being divided into organ systems.”2 Now more than ever, patients need generalist doctors who can put their individual problems in context and provide continuity. In the Renaissance School of General Medicine students will learn only what they need to learn to be supremely effective generalists. From day one the …
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.125 | 0.038 |
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".