William Osler at McGill University: the Baby Professor and his early contributions to neurosurgery
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Between 1870 and 1884, as both a medical student and a member of the faculty, Sir William Osler performed approximately 1000 postmortem examinations at McGill University in Montreal. He conducted 786 of these examinations during his 7 years (1877--1884) of service as a pathologist at the Montreal General Hospital. The results of these were carefully recorded and catalogued either by him or by those who compiled the Pathological Report of the Hospital. Included in this material are many early descriptions of neurosurgical disease. Osler used this information for subsequent teaching in both Philadelphia and Baltimore. Osler's early and lifelong special interest in diseases of the nervous system not only led him to make seminal observations but also served to initiate his influence and relationships with the emerging leaders in neurology and neurosurgery.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it