Acute effects of raisin consumption on glucose and insulin reponses in healthy individuals
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
Raisins are popular snacks with a favourable nutrient profile, being high in dietary fibre, polyphenols and a number of vitamins and minerals, in addition to being rich in fructose. In light of evidence demonstrating improvements in glycaemic control with moderate fructose intake and low-glycaemic index (GI) fruits, our aim was to determine the GI, insulin index (II) and postprandial responses to raisins in an acute feeding setting. A total of ten healthy participants (four male and six female) consumed breakfast study meals on four occasions over a 2- to 8-week period: meal 1: white bread (WB) (108 g WB; 50 g available carbohydrate) served as the control and was consumed on two separate occasions; meal 2: raisins (R50) (69 g raisins; 50 g available carbohydrate); and meal 3: raisins (R20) (one serving, 28 g raisins; 20 g available carbohydrate). Postprandial glucose and insulin were measured over a 2 h period for the determination of GI, glycaemic load (GL) and II. The raisin meals, R50 and R20, resulted in significantly reduced postprandial glucose and insulin responses when compared with WB (P < 0·05). Furthermore, raisins were determined to be low-GI, -GL and -II foods. The favourable effect of raisins on postprandial glycaemic response, their insulin-sparing effect and low GI combined with their other metabolic benefits may indicate that raisins are a healthy choice not only for the general population but also for individuals with diabetes or insulin resistance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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