Acute effects of extruded pea fractions on glycemic response, insulin, appetite, and food intake in healthy young adults, results of a double-blind, randomized crossover trial
Bibliographic record
Abstract
Benefits of pulse consumption on glycemic control are well established; however, research examining the effects of pulse fractions incorporated into extruded products is limited. In a randomized, repeated-measures crossover study, adults (n = 26) consumed cereals made with oat flour (control), oat flour and pea starch (starch), oat flour and pea protein (protein), oat flour, pea starch and pea protein (starch+protein), oat flour, pea fibre and pea protein (fibre+protein), and pea fibre, pea starch and pea protein (fibre+starch+protein). Blood glucose (BG) and insulin concentrations, and appetite incremental area under the curve (iAUC) were calculated before (0–120 min) and after (120–200 min) the ad libitum meal for measurement of food intake. Pre-meal, overall mean BG and iAUC were lower following the protein, starch+protein, protein+fibre, and the fibre+starch+protein cereals compared with the starch and control. For pre-meal overall mean insulin concentrations, fibre+protein led to a lower response compared with control, starch+protein, and protein cereals. Fibre+starch+protein also led to lower insulin compared with protein cereal. Pre-meal insulin iAUC was lower following fibre+protein compared with control and protein cereals. The inclusion of yellow pea protein and fibre in oat-based breakfast cereal reduces postprandial glycemia; however this effect is dependent on fraction type. ClinicalTrials.gov: NCT02366572. Novelty: Inclusion of pulse protein and fibre in oat flour-based breakfast cereal reduces postprandial glucose response. The glycemic benefits of whole pulses are at least somewhat retained in some pulse fractions.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| 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 | 0.002 |
| 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".