Evolutionary medicine: update on the relevance to family practice.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To review the relevance of evolutionary medicine to family practice and family physician training. QUALITY OF EVIDENCE: Articles were located through a MEDLINE search, using the key words evolution, Darwin, and adaptation. Most references presented level III evidence (expert opinion), while a minority provided level II evidence (epidemiologic studies). MAIN MESSAGE: Evolutionary medicine deals with the interplay of biology and the environment in the understanding of human disease. Yet medical schools have virtually ignored the need for family physicians to have more than a cursory knowledge of this topic. A review of the main trends in this field most relevant to family practice revealed that a basic knowledge of evolutionary medicine might help in explaining the causation of diseases to patients. Evolutionary medicine has also proven key to explaining the reasons for the development of antibiotic resistance and has the potential to explain cancer pathogenesis. As an organizing principle, this field also has potential in the teaching of family medicine. CONCLUSION: Evolutionary medicine should be studied further and incorporated into medical training and practice. Its practical utility will be proven through the generation of testable hypotheses and their application in relation to disease causation and possible prevention.
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.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it