Pairing nuts and dried fruit for cardiometabolic health
Bibliographic record
Abstract
Certain dietary patterns, in which fruits and nuts are featured prominently, reduce risk of diabetes and cardiovascular disease. However, estimated fruit consumption historically in the U.S. has been lower than recommendations. Dried fruit intake is even lower with only about 6.9 % of the adult population reporting any consumption. The 2015 Dietary Guidelines Advisory Committee identified a gap between recommended fruit and vegetable intakes and the amount the population consumes. Even fewer Americans consume tree nuts, which are a nutrient-dense food, rich in bioactive compounds and healthy fatty acids. Consumption of fruits and nuts has been associated with reduced risk of cardiometabolic disease. An estimated 5.5 to 8.4 % of U.S. adults consume tree nuts and/or tree nut butter. This review examines the potential of pairing nuts and dried fruit to reduce cardiometabolic risk factors and focuses on emerging data on raisins and pistachios as representative of each food category. Evidence suggests that increasing consumption of both could help improve Americans' nutritional status and reduce the risk of chronic diseases.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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".