Bibliographic record
Abstract
Aortic valve stenosis (AS) is the most common valvular heart disease in the Western world, affecting about 3% of the population over 75 years of age and after onset of symptoms is associated with adverse events including death.1 With the ageing of the population, AS likely will become an increasingly important health issue. Despite this grim prospect, a therapeutic strategy to slow the progression of AS has not been developed and the only effective treatment is aortic valve replacement. Furthermore, AS is a progressive condition, but the rate of progression is quite variable from individual to individual. The predilection of AS in the older individuals has led to the belief that AS was an inevitable result of a degenerative process, but research has shown that it is an active process involving multiple metabolic pathways, raising the possibility that the process can potentially be modified or interrupted.2 Epidemiological studies have shown that AS is associated with traditional atherosclerotic risk factors such as hypertension, smoking, diabetes and increased cholesterol. At the molecular level, AS also shares common features with atherosclerosis including lipid infiltration, inflammation, fibrosis and calcification in the subendothelial space and lamina fibrosa. Since lipoproteins are involved in several putative pathways in the development of AS, lipid-lowering agents such as statins would be expected to …
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".