Acute effects of extruded pulse snacks on glycemic response, insulin, appetite, and food intake in healthy young adults in a double blind, randomized, crossover trial
Bibliographic record
Abstract
Research indicates that the postprandial glycemic benefits of consuming whole pulses are retained when consumed in a mixed meal, pureed, and ground into flours. The glycemic benefits of pulse flours when incorporated into extruded products are unknown. In a randomized, repeated-measures crossover study, adults (n = 26) consumed extruded corn snacks made with the addition of 40% pulse flour from either whole yellow pea, split yellow pea, green lentil, chickpea, or pinto bean. The control snack was 100% corn. Food intake was measured with an ad libitum meal consumed at 120 min. Blood glucose (BG), insulin and appetite were measured regularly before (pre-meal, 0–120 min) and after (post-meal, 140–200 min) the meal. Pinto bean and chickpea snacks led to lower (p < 0.05) pre-meal BG incremental area under the curve (iAUC), compared with control, whole yellow pea and green lentil snacks. Pinto bean snack also led to lower (pre-meal BG (p < 0.05) and insulin (p < 0.05) iAUC compared with control, whole yellow pea, and split yellow pea snacks. There were no differences in food intake or appetite. These findings indicate that effects of replacing corn with pulse flours in extruded snacks on BG, and insulin are dependent on pulse type. ClinicalTrials.gov Identifier: NCT02402504. Registered on 30 March 2015. Novelty: The incorporation of pinto bean and chickpea flour into extruded corn snacks improves postprandial glycemic response. Pulse containing snacks were equally as palatable as the corn snacks. The incorporation of pulses into corn snacks increased the protein and fibre content.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".