Bibliographic record
Abstract
Maria Daria Haust, MD, has made many significant contributions to our understanding of atherogenesis in children, particularly in associating the earliest lesions (fatty spots and streaks) with the normal growth and remodeling of arteries. It is my privilege to link her early work to more recent findings which show that the early lesions seen in the arteries of children before puberty bear no relationship to the risk of atherosclerosis in later life. Furthermore, present evidence supports the view that intervening in childhood (2-15 years) with low-fat low-cholesterol diets or even worse, lipid-lowering drugs to prevent atheroslerotic plaques in adulthood is wasted effort. Overzealous parents may unwittingly induce malnutrition in their children and many children with restricted access to palatable foods, will yearn for them even more as they become older leading to over weightness. Pediatricians from various scientific bodies around the world vary in their advice to mothers regarding diets for children. The program adopted by Health Canada on the advice of pediatricians in that country, which is also supported by the European Society of Pediatrics, Gastroenterology and Nutrition, recommends that the fat content of diets for children should be tapered gradually from 40% of energy at 2 years of age to 30% of energy at the conclusion of linear growth (late adolescence).
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".