millet has a very small amount of floury endosperm and barley, and rice [55]. The endosperm protein fraction of has both simple and compound starch granules [181]. Teff pearl millet contains low levels of lysine (1.4 g/100 g pro-has primarily simple starch granules with a small percent-tein), whereas the germ contains 5.16 g/100 g protein [2]. age of compound ones [127]. Pearl millet, fonio, and fox-Among millets, pearl and finger millets usually have the tail millet have simple starch granules only [82,127]. most lysine (Table 5). Teff and kodo millets are also high The germ can be large relative to the endosperm, as in in lysine. Proso and Japanese millets have the poorest es-pearl millet or fonio, or very small, as in proso and finger sential amino acid composition. However, when germinat-millets (Table 3). The pearl millet germ contains 24.5, ed, proso millet demonstrated an increase in lysine, trypto-32.8, and 7.2% of the total protein, fat, and ash found in phan, and other free amino acids as well as nonprotein the kernel, respectively [2]. nitrogen levels [147]. There were also increases in albu-mins and globulins and large decreases in prolamines [148]. Proteins in finger millets were better balanced than those in common and foxtail millets [159]. They also re-ported that the antitryptic activities if these millets were
Bibliographic record
Abstract
The United States, Canada, and the United Kingdom have had a cereal enrichment program for over 50 years. Some of the discoveries and events that led to the adoption of the program in the United States [ 1 ] are: The discovery in the early 1900s that certain chemical compounds (vitamins) and minerals in foods are essential for good health. The synthesis of thiamine by R. A. Williams in 1936. The reduced cost of synthetic vitamins made enrichment economically feasible. The finding that a large proportion of the vitamins and minerals naturally occurring in wheat were being removed by the milling process [ 2 ]. The alarming incidence of nutritional deficiency diseases, especially pellagra (niacin deficiency), among the poorer population groups of the United States. The early advocation by James F. Bell of the General Mills Company, Dr. Russell Wilder of the American Medical Association (AMA), and other influential voices for cereal enrichment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".