When Is Knowledge Ripe for Primary Care?
Bibliographic record
Abstract
The objectives of this study were to explore the meaning of scientific evidence as it is understood by primary care physicians. Individual interviews were conducted with actors chosen for their roles in the production and use of knowledge: 22 family physicians, 13 specialist physicians, and 6 researchers. Two situations served as points of reference for these discussions: screening for genetic breast cancer and treatment of hypertension. The results suggest that there may be a misunderstanding between the producers of knowledge and primary care practitioners with respect to what constitutes "evidence"--knowledge ready for integration into the clinical practice of primary care. These potential differences go beyond the issues of how information is disseminated. Rather, many of the questions raised by family physicians concern how knowledge is developed. In the interests of fostering better dissemination of new knowledge and encouraging its adoption, new links should be created between knowledge "producers" and potential users.
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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 | 0.068 | 0.192 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.010 | 0.035 |
| Scholarly communication | 0.028 | 0.028 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".