Bibliographic record
Abstract
During the 1970s some investigators proposed that refined carbohydrates, especially sugar and a low intake of dietary fiber, were major factors in coronary heart disease (CHD). This suggestion was eclipsed by the belief that an excess intake of saturated fatty acids (SFA) was the key dietary factor, a view that prevailed from roughly 1974 to 2014. Findings that have accumulated since 1990 inform us that the role of SFA in the causation of CHD has been much exaggerated. A switch from SFA to refined carbohydrates does not lower the ratio of total cholesterol to HDL-cholesterol in the blood and therefore does not prevent CHD. A reduced intake of SFA combined with an increased intake of polyunsaturated fatty acids lowers the ratio of total cholesterol to HDL-cholesterol; this may reduce the risk of CHD. The evidence linking carbohydrate-rich foods with CHD has been steadily strengthening. Refined carbohydrates, especially sugar-sweetened beverages, increase the risk of CHD. Conversely, whole grains and cereal fiber are protective. An extra one or 2 servings per day of these foods increases or decreases risk by approximately 10% to 20%.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".