Bibliographic record
Abstract
The term “evidence based medicine” was coined in 1992 to label a clinical learning strategy, which the teaching staff of the Faculty of Health Sciences at McMaster University in Canada has been developing for over a decade [1,2]. In the years that followed, this novel idea shifted from how to read the medical literature to how to apply the medical literature to the care of the individual patient and under its new form, it has expanded as a real movement, with an impact on education, policy making and research. A comprehensive review published in this issue provides explicit insight into various aspects of the topic [3]. Tracing the history of evidence based medicine, the author seems to adopt the suggestion made by the McMaster’s pioneers that the new doctrine has its origins in mid-19th century Paris [4] or as worded by PK Rangachari, that evidence based medicine is an “old French wine with a new Canadian label” [5]. There is no doubt that the publication in 1835 of the study of the French doctor Pierre Louis on the effectiveness of blood-letting for the treatment of pneumonia can be regarded as a landmark in the evolution of Clinical Epidemiology. However, although outcomes research is an integral part of evidence based medicine, the philosophy of the new clinical discipline in its original formulation extends beyond randomised trials and meta-analyses [4]. In essence, the new concept lies in distinguishing between the use of evidence from clinical research to make decisions and the cause-and-effect reasoning of traditional medical science [6]. In this respect, the first mention of the distinction between evidence based medicine and inferential reasoning extends back to the fifth century BC, when Hippocrates advised his contemporary physicians to “rely on actual evidence rather than on conclusions resulting solely from reasoning, because arguments in the form of idle words are erroneous and can be easily refuted”. (“Oui a’ uo euaio iuiio ioiðanaeiiiÝiui ic asc aðaýnaoeae , oui aa uo Ýnaio aiaasieio ooaeanÞ aan eae aýðoaeooio c iao’ aaieao÷sco eo÷ýneoeo», Ðanaaaaesae EE). Some of the opponents of evidence based medicine argue that there is nothing new in this idea since medicine was always evidence-based. A caustic comment published in the correspondence column of the Lancet ten years ago [7], pointed out that: “Evidence-based medicine is a neologism for informed decision making, and this example of newspeak would have delighted George Orwell. The presumption is made that the practice of medicine was previously based on a direct communication with God or by tossing a coin.” The truth is, however, that before the era of evidence-based medicine, most of the physicians were well trained in biology, but they received little formal training to help evaluate the information that does exist. As a consequence, the practice of medicine was largely based on assumptions and pathophysiological rationale. A characteristic example of this way of making decisions is provided by two passages concerning the treatment of shock taken from the third edition of Friedberg’s EDITORIAL
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 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".