Bibliographic record
Abstract
HYPERTENSIONHypertension is commonly associated with other cardiovascular risk factors such as obesity, diabetes, and dyslipidemia.Observational studies that incorporate treating several of these risk factors simultaneously have found improvement in cardiovascular outcomes in individuals with established hypertension.The presence of these risk factors commonly results in endothelial dysfunction.Whether their presence results in the future development of hypertension has been unclear.To evaluate whether the presence of hyperlipidemia contributes to the future development of hypertension, investigators from the Physicians' Health Study prospectively examined healthy male physicians to determine whether total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and non-high-density lipoprotein cholesterol (non-HDL-C) increase the risk of developing future hypertension.The National Cancer Institute and the National Heart, Lung, and Blood Institute study enrolled 22,071 male physicians between the ages of 40 and 84 years (average age, 48 years) in 1982.Of these, 3110 subjects had measurements of TC and HDL-C and were initially free from hypertension (systolic blood pressure [BP] <140 mm Hg or diastolic
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 | 0.005 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.024 | 0.042 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.102 | 0.023 |
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".