William Osler (1849–1919) at the Roots of Evidence-Based Medicine
Bibliographic record
Abstract
2019 marks the centenary of the death of William Osler, a Canadian by birth and internationally regarded as a leading physician of his time. His work, in Canada, the US, and the UK and eloquent writings spread his knowledge, thinking and way of practicing and teaching medicine. He advocated for the patient, rather than the disease, as the focus of medical practice, and his writings demonstrate his concerns for matching practice to the patient’s circumstances and expectations, honing the physician´s clinical skills, and using the best scientific evidence available at the moment. Osler’s approach is regarded by many as the beginning of modern medicine and has some interesting coincidental and intentional connections with evidence-based medicine (EBM) of current times. By coincidence, Osler was raised in Dundas, now part of Hamilton, Ontario, the eventual home of David Sackett, a Canadian by choice, who led the current era of EBM. Both began their academic careers at Canadian universities and ended their careers as professors at the University of Oxford. By intention, EBM emphasizes a critical mind, appraisal, and use of the scientific literature, and incorporation of the patient’s circumstances and preferences in reaching clinical decisions. The clinical epidemiologic science that underpins EBM is quite different from the observational pathophysiologic reasoning of Osler, and Osler may or may not have approved. In any event, many of his writings hold true for current medical practice.
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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".