Bibliographic record
Abstract
Progress in the medical sciences is largely determined by two things: (i) the questions we ask, and (ii) how rigorously and vigorously we attempt to answer them. How do we know which questions are the right questions to ask, and thus the correct questions to spend our time and energies trying to answer? Such evaluative concerns bring into sharper focus the question--'What is medicine for?' The international study of rosuvastatin is important not simply because of the health benefits it may confer, but because it inspires a more robust and inclusive vision of the medical sciences. A vision which recognizes that the primary goal of medicine is to promote health, and that includes the health of 'normal' people as well as those with illness and disease. This inclusive vision of the medical sciences is a transformative one, it departs from the 'disease-model' approach which has dominated distinct areas of medical research for decades.
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 | 0.175 | 0.060 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.016 | 0.005 |
| Science and technology studies | 0.016 | 0.130 |
| Scholarly communication | 0.056 | 0.052 |
| Open science | 0.005 | 0.033 |
| Research integrity | 0.024 | 0.067 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".