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
The health risks associated with consumption of diets high in trans fats from industrially produced hydrogenated fats are well documented. However, trans fatty acids are not a homogeneous group of molecules, and less is known about the health effects of consuming diets containing vaccenic acid (VA), a positional and geometric isomer of oleic acid, the predominant trans isomer in ruminant fats. The presence of VA in industrial trans fats has raised the question of whether VA produces the same adverse health effects as industrially produced trans fats. VA is also the major trans fat in ruminant fats, and questions have arisen as to whether consuming this trans fat has the same effects on health risk. The purpose of this paper is to critically review the published studies in humans, animals, and cell lines. Epidemiological, but not rodent, studies suggest that VA intake or serum concentrations may be associated with increased cancer risk. However, epidemiological, clinical, and rodent studies to date have not demonstrated a relationship with heart or cardiovascular disease, insulin resistance, or inflammation. VA is the only known dietary precursor of c9,t11 conjugated linoleic acid (CLA), but recent data suggest that consumption of this trans fat may impart health benefits beyond those associated with CLA.
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) | 0.003 | 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 | 0.001 |
| 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