Health Benefits of Vegetarian Diets: An Insight into the Main Topics
Bibliographic record
Abstract
Vegetarian diets are plant-based diets including all the edible foods from the Plant Kingdom, such as grains, legumes, vegetables, fruits, nuts, and seeds. Dairy and eggs can be added in small amounts in the lacto-ovo-vegetarian subtype, or not at all in the vegan subtype. The abundance of non-processed plant foods-typical of all well-planned diets, including vegetarian ones-can provide the body with numerous protective factors (fiber, phytocompounds), while limiting the intake of harmful nutrients like saturated fats, heme-iron, and cholesterol. The beneficial effects on health of this balance have been reported for many main chronic diseases, in both observational and intervention studies. The scientific literature indicates that vegetarians have a lower risk of certain types of cancer, overall cancer, overweight-obesity, type 2 diabetes, dyslipidemia, hypertension, and vascular diseases. Since the trend of following a vegetarian diet is increasing among citizens of developed countries, the knowledge in the field will benefit from further studies confirming the consistency of these findings and clarifying the effects of vegetarian diets on other controversial topics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".