Bibliographic record
Abstract
The health care community has lost a remarkable human being who had a profound impact on research methodology and the way clinical practice has evolved over the past 5 decades. Dr. David Sackett (Figure), recognized as the father of evidence-based medicine (practice) (EBM), died on May 13, 2015. Evidence-based medicine (practice) is defined as “the integration of best research evidence with clinical expertise and patient values”1,2 and was ranked by BMJ as one of the top 10 medical breakthroughs since 1840.3 Figure. David L. Sackett, OC, FRSC, MD, MSc(Epidemiology), ScD, FRCP (Canada, London, Edinburgh). Professor Emeritus, McMaster University, Hamilton, Ontario, Canada. Sackett was born in Chicago and received a medical degree from the University of Illinois and a master's degree in epidemiology from Harvard University. His original medical training was in internal medicine and nephrology; however, at the time of the Cuban Missile Crisis, he was drafted and assigned to the US Public Health Service (USPHS). It was during his experience with the USPHS that he began to conceive how epidemiological principles could be applied to clinical practice. “Big-E” epidemiology examines the distribution and determinants of disease and injury in populations, whereas clinical epidemiology is concerned with the determinants and effects of clinical decisions. The following is a brief account of Sackett's career in his own words and edited by Dr. Brian Haynes. It appeared in an interview-style document that he wrote in response to questions about his career: After training in internal medicine, nephrology and epidemiology, David Sackett re-coined the term “clinical epidemiology” and began his 1st career (age 32) as the founding Chair of Clinical Epidemiology & Biostatistics at McMaster University's new medical school. In his 2nd career he began to design, execute, …
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".