The Evidence-based Medicine Paradigm: Where are We 20 Years Later? Part 1
Bibliographic record
Abstract
The evidence-based medicine (EBM) paradigm, introduced in 1992, has had a major and positive impact on all aspects of health care. However, widespread use has also uncovered some limitations; these are discussed from the perspectives of two clinicians in this, the first of a two part narrative review. For example, there are credible reservations about the validity of hierarchical levels of evidence, a core element of the EBM paradigm. In addition, potential and actual methodological and statistical deficiencies have been identified, not only in many published randomized controlled trials but also in systematic reviews, both rated highly for evidence in EBM classifications. Ethical violations compromise reliability of some data. Clinicians need to be conscious of potential limitations in some of the cornerstones of the EBM paradigm, and to deficiencies in the literature.
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 | 0.047 | 0.105 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.013 | 0.029 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.010 | 0.018 |
| Insufficient payload (model declined to judge) | 0.008 | 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".