Chemical and Physical Characteristics of Proso Millet (<i>Panicum miliaceum</i>)‐Based Products
Bibliographic record
Abstract
Celiac disease and gluten sensitivities, as well as obesity and overweight‐related disorders, have led to the investigation of gluten‐free grains and development of new food products. To address this, refined proso millet and refined corn (control), both gluten‐free grains, were used to produce four different product types (muffin, couscous, extruded snack, and porridge). The products contained four different grain combinations (100% proso millet, 75% proso millet/25% corn, 25% proso millet/75% corn, and 100% corn). All products were evaluated for their nutritional composition, in vitro starch digestibility, and expected glycemic index (eGI). Products made with refined proso millet had increased protein (7.6–11.3%), lipid (1.2–6.1%), fiber (7.0–8.8%), and phenolic content (323.5–425 μg/g) compared with those incorporating corn flour (2.5–9.0%, 0.8–4.0%, 2.1–4.1%, and 213–315 μg/g, respectively). As the proso millet content increased, the eGI decreased significantly (P < 0.05). Products made from refined proso millet appear to be good candidates for producing low‐GI, gluten‐free foods.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".