An Evidence Base for Heart Disease Prevention using a MediterraneanDiet Comprised Primarily of Vegetarian Food
Bibliographic record
Abstract
Dietary patterns, nutrition, physical activity, air pollution, tobacco smoke, ethnicity and genetics affect heart disease. Vegetarian food diets are one of the important factors in its prevention and control. People living in the five blue zones, mostly consuming the Mediterranean diet (MedDiet), have the highest longevity in the world and the least incidence of heart disease. There are several forms of heart pathology, e.g., the most common coronary heart disease, myocardial infarction, congestive heart failure, heart valve disease and abnormal heart rhythms. Heart disease is the leading cause of death in the world and varies by race, where indigenous and people of color have a higher risk for its complications than the white population. The morbidity of cardiovascular pathology in the Afro-American community persists high and is a primary source of disparities in life expectancy between Afro-Americans and whites in the United States. Adherence to healthy diets higher in vegetable foods and lower in animal foods is correlated with a lower risk of cardiovascular disease, morbidity and mortality in the general population. A detailed literature review was performed of the Medline, EMBASE, and Ebsco databases to synthesize and compare evidence on this topic to produce a review of the importance of a Mediterranean diet in the prevention of heart disease. Consumption of a MedDiet consisting of fruits and vegetables (including berries due to their high fibre and antioxidant content), nuts, whole grains, leafy greens, beans like chickpeas, eggplants, Greek yogurt and extra virgin olive oil are associated with longer life and lower incidence of heart disease. The latter diet is superior to consuming large quantities of meat and refined carbohydrates, such as sucrose, high fructose corn syrup and grains that have had the fibrous and nutritious parts removed.
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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 | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".