Bibliographic record
Abstract
n 2003, Wald and Law 1 predicted that coronary artery disease (CAD) would be markedly attenuated if not eliminated.CAD is a preventable disease based on randomized, placebo-controlled clinical trials that consistently showed 30% to 40% reduction in cardiac events with decreased plasma cholesterol.1 Epidemiologists claimed for decades that 40% to 50% of predisposition for CAD is genetic.Discovery of the first genetic risk variant in 2007 has led to an avalanche of >90 genetic risk variants predisposing to CAD, each of genome-wide significance and replicated in independent populations, 2 but each with relatively low individual effect sizes.The total individual genetic risk burden for CAD is proportional to the number of genetic risk variants inherited.These variants account for ≈25% of genetic predisposition to CAD, which is less than the predicted 40%, signaling that more genetic risk variants are yet to be discovered.It is interesting to note that only one third of the genetic risk variants for CAD mediate their risk through known conventional risk factors.Exploration of the unknown pathways mediating the risk conferred by these genetic variants is already enabling new insights into the pathogenesis of coronary atherosclerosis (eg, inflammation, lack of protection of high-density lipoprotein cholesterol) and novel targets for the development of specific drugs.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".