Development of Low Glycemic Index (GI) Foods by Incorporating Pulse Ingredients into Cereal‐Based Products: Use of In Vitro Screening and In Vivo Methodologies
Why this work is in the frame
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Bibliographic record
Abstract
Pulse ingredients (pea and lentil flour, pea protein, and pea fiber) were incorporated into 94 different food products. Products included pastas, breads, crackers, extruded snacks, cookies, cereal bars, and muffins. Products were screened for estimated glycemic index using an in vitro method. Based on the screening results, five products (pasta, bread, cracker, granola bar, and cookie) were selected for in vivo glycemic index (GI) testing. For each control (containing 100% wheat flour), a pulse variant (containing up to 50% pulse ingredients) was developed. Ten healthy subjects consumed each test meal in addition to three control white bread meals on separate days during the in vivo GI testing. GI values of the control and pulse variant meals were 61.3 ± 5.1 versus 54.6 ± 7.6 (pasta), 61.4 ± 5.6 versus 53.4 ± 4.7 (focaccia bread), 46.0 ± 4.2 versus 41.5 ± 3.1 (cracker), 35.4 ± 3.6 versus 34.8 ± 5.0 (granola bar), and 41.6 ± 3.8 versus 37.6 ± 3.0 (cookie). The difference did not reach statistical significance ( P > 0.05). Mean GI difference between control and pulse variant was 4.8 ± 2.6, with all pulse variants falling into the low GI category. Palatability scores showed no statistically significant difference ( P > 0.05) between the control and pulse variant. The data support substituting wheat flour with pulse ingredients to reduce the GI value without changing palatability of the products.
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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 | 0.000 | 0.000 |
| 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