Bibliographic record
Abstract
During his surgical career between 1896 and 1934, Harvey Cushing made eight visits to Canada. He had a broad impact on Canadian medicine and neurosurgery. Cushing's students Wilder Penfield and Kenneth McKenzie became outstanding leaders of the two major centers in Canada for neurosurgical treatment and training. On his first trip to Canada, shortly after completing his surgical internship in August 1896, Cushing traveled with members of his family through the Maritime Provinces and visited hospitals in Quebec and Montreal. Eight years later, in February 1904, as a successful young neurosurgeon at the Johns Hopkins Hospital, he reported to the Montreal Medico-Chirurgical Society on his surgical experience in 20 cases of removal of the trigeminal ganglion for neuralgia. In 1922, as the Charles Mickle Lecturer at the University of Toronto, Cushing assigned his honorarium of $1000 to support a neurosurgical fellowship at Harvard. This was awarded to McKenzie, then a general practitioner, for a year's training with Cushing in 1922-1923. McKenzie returned to initiate the neurosurgical services at the Toronto General Hospital, where he developed into a master surgeon and teacher. On Cushing's second visit to McGill University in October 1922, he and Sir Charles Sherrington inaugurated the new Biology Building of McGill's Medical School, marking the first stage of a Rockefeller-McGill program of modernization. In May 1929, Cushing attended the dedication of the Osler Library at McGill. In September 1934, responding to the invitation of Penfield, Cushing presented a Foundation Lecture-one of his finest addresses on the philosophy of neurosurgery-at the opening of the Montreal Neurological Institute. On that same trip, Cushing's revisit to McGill's Osler Library convinced him to turn over his own treasure of historical books to Yale University.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.103 | 0.021 |
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".