Pairing nuts and dried fruit for cardiometabolic health
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it