What is Evidence-Based Medicine and Why Should it be Practiced?
Bibliographic record
Abstract
Responding to the limitations of traditional expert recommendations as a guide to clinical practice, evidence-based medicine has presented a paradigm shift in the way clinicians learn and practice medicine. The practice of evidence-based medicine requires careful examination of the evidence, using a set of formal rules applied in an explicit manner. The clinician then judiciously applies the evidence to decision-making, with an understanding of the patient context and values. Using examples pertinent to respiratory therapists, we discuss evidence-based decision-making as a clinical problem-solving strategy, its basis on a hierarchy of evidence, and the interplay of values, preferences, expertise, and circumstances that affect its application. We briefly describe some resources available to obtain evidence reports and to learn to critically appraise and apply them.
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 | 0.124 | 0.383 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.004 | 0.022 |
| Scholarly communication | 0.018 | 0.023 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.015 | 0.016 |
| Insufficient payload (model declined to judge) | 0.005 | 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".