Bibliographic record
Abstract
Stroke is one of the leading causes of mortality and disability, with major socioeconomic impact, particularly in developed countries.3 There is a twofold higher risk of cardiac-related mortality compared with agematched controls,4 and the 5- and 10-year rates for recurrent stroke are 26% and 40%, respectively.5 Interventions that target modifiable cardiovascular risk factors, such as hypertension, smoking status, body composition, and physical activity, may reduce the burden of stroke.6 For the general population, the benefits of improved physical fitness on a myriad of health outcomes are well established. Physical fitness includes components such as cardiorespiratory fitness, muscle strength and endurance, flexibility, and body composition. 7 Higher levels of fitness are associated with reduced risk for all-cause and cardiovascularrelated mortality, 8,9 cardiovascular disease, 10 and stroke, 11 and aerobic exercise training has been shown to improve a number of vascular risk factors. 12‐14
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".