Bibliographic record
Abstract
Abstract When Willie Osler entered Trinity College School in Weston in 1866, he was a happy-go-lucky sixteen-year-old. He liked hunting, sports, and fights with the day boys and villagers. Smallish – he had probably reached his adult height of five foot, five and three-quarter inches – but wiry and fit, he was a good athlete, known for the strength and accuracy of his throwing arm: ‘Last Friday I was coming up and the Roman Catholic school was standing about 80 yards from the road and I bet a boy I could throw and break a window. The other fellow threw and did not come near it ... Mine went through the window and struck one of the boys on the head, there was a terrible row about it but I went down to the old Priest and made it all right and put in the window.’ Willie took to the English-style discipline (a prefect system and liberal caning by the masters) of the newly founded Trinity College School; he liked his schoolmates, found headmaster Badgely ‘firstrate’ and the singing lessons and theatricals ‘such jolly fun.’ His mother disapproved of such ‘mummeries’ as being too worldly.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.112 | 0.017 |
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".