Calgary, Edmonton and the University of Alberta: the extraordinary medical mobilization by Canada’s newest province
Bibliographic record
Abstract
SUMMARY: The Canadian contribution of medical services to the British Empire during the First World War was a national endeavour. Physicians from across the country enlisted in local regiments to join. No other region provided more physicians per capita than the newly formed province of Alberta. Largely organized through the Medical School of the University of Alberta, the No. 11 Canadian Field Ambulance out of Edmonton and the No. 8 Canadian Field Ambulance out of Calgary ultimately enlisted between one-third and half of the province's doctors to the war campaign. Many individuals from this region distinguished themselves, including LCol J.N. Gunn from Calgary, who commanded the No. 8 Canadian Field Ambulance; Maj Heber Moshier, one of the founders of the School of Pharmacy at the University of Alberta; and Dr. A.C. Rankin, who would go on to be the first Dean of Medicine at the University of Alberta. These Canadian heroes, and the many others like them who served with the No. 8 and 11 Field Ambulances, personify the sacrifice, strength and resilience of the medical community in Alberta and should not be forgotten.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.007 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".