Bibliographic record
Abstract
BACKGROUND: Since its inception 50 years ago, the Canadian Journal of Surgery has published articles under the banner "History of Canadian Surgery." Because no comprehensive history of surgery in this country has yet been written, these articles may provide its basis. METHOD: The Canadian Journal of Surgery was searched from October 1957 to August 2007 for articles on the practice of surgery in Canada before 1957. Articles regarding the development of surgery in provinces, universities, hospitals and surgical specialty societies were included, as well as biographies and obituaries of surgeons. RESULTS: Thirty-six articles dealing with the lives of 57 Canadian surgeons were located. Three periods of Canadian surgery were covered: the French regime (1535-1759), the transition period (1759-1870) and the early modern period (1870-1945). The review shows that persistent efforts were made in Canada to develop surgical education and to regulate the practice of surgery. Isolation forced a spirit of adaptability that led to innovation and progress. CONCLUSION: The practice of surgery in Canada today can be traced back to contributions made by pioneering surgeons over the entire history of modern Canada. An archive of materials related to the history of surgery in Canada is being created at www.historyofsurgery.ca to facilitate further research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.060 | 0.008 |
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".