Top 20 research studies of 2013 for primary care physicians.
Bibliographic record
Abstract
In 2013, we performed monthly surveillance of more than 110 English-language clinical research journals, and identified approximately 250 studies that had the potential to change the practice of family physicians. Each study was critically appraised and summarized by a group of primary care clinicians with expertise in evidence-based medicine. Studies were evaluated based on their relevance to primary care practice, validity, and likelihood that they could change practice. These summaries, called POEMs (patient-oriented evidence that matters), are e-mailed to subscribers, including members of the Canadian Medical Association. A validated tool was used to obtain feedback from these physicians about the clinical relevance of each POEM and the benefits the physicians expected for their practice. This article, the third installment in this annual series, summarizes the 20 POEMs judged to have the greatest clinical relevance. The included POEMs address questions such as whether patients must fast before measurement of lipids (no), whether a Mediterranean diet reduces mortality (yes), and the likelihood of clinically important bleeding in older patients taking warfarin (3.8% per year).
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 | 0.022 | 0.102 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.045 | 0.031 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.037 | 0.008 |
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".