Mediterranean diet impact on cardiovascular diseases
Bibliographic record
Abstract
: Cardiovascular disease (CVD) accounts for more than 17 million deaths per year worldwide. It has been estimated that the influence of lifestyle on CVD mortality amounts to 13.7% for smoking, 13.2% for poor diet, and 12% for inactive lifestyle. These results deeply impact both the healthy status of individuals and their skills in working. The impact of CVD on productivity loss accounts for the 24% in total costs for CVD management.Mediterranean diet (MedD) can positively impact on natural history of CVD. It is characterized by a relatively high consumption of inexpensive and genuine food such as cereals, vegetables, legumes, nuts, fish, fresh fruits, and olive oil as the principal source of fat, low meat consumption and low-to-moderate consumption of milk, dairy products, and wine.Its effects on cardiovascular health are related to the significant improvements in arterial stiffness. Peripheral artery disease, coronary artery disease, and chronic heart failure are all positively influenced by the MedD. Furthermore, MedD lowers the risk of sudden cardiac death due to arrhythmias.The present narrative review aims to analyze the effects of MedD on CVD.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.005 | 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".