Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Noninvasive measures of atherosclerosis, such as carotid intima-media thickness, total carotid plaque area, and carotid stenosis, probably represent different phenotypes with distinct determinants. For instance, total carotid plaque area may reflect atherosclerotic lesion size more closely than carotid stenosis, which instead may reflect hemodynamic compromise within the arterial lumen. METHODS: In 1821 patients from a Premature Atherosclerosis Clinic, we studied determinants of total carotid plaque area and carotid stenosis as measured by ultrasound using multivariate regression analysis with traditional risk factors and some emerging risk factors. RESULTS: Regression modeling showed that (1) traditional atherosclerosis risk factors were more strongly associated with total carotid plaque area than with carotid stenosis (R=0.53 and 0.13, respectively), and (2) individual risk factors had different relationships with total carotid plaque area and carotid stenosis. For instance, age accounted for 53% and 26% of the explained variance of total carotid plaque area and carotid stenosis, respectively. Female sex was inversely associated with total carotid plaque area but positively associated with carotid stenosis. Nontraditional risk variables such as plasma homocysteine had different associations with the 2 analytes. CONCLUSIONS: Total carotid plaque area and carotid stenosis had different associations with specific atherosclerosis risk factors. Thus, for future studies of the determinants of atherosclerosis, it is important to distinguish between different phenotypes and to appreciate that they will not necessarily have the same determinants.
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.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it