Bibliographic record
Abstract
The ultimate goal of this research is to characterize data from the laboratory, pilot, and industrial scale rice mills. Pilot and laboratory scale data are presented in this research. Two long grain rice cultivars were milled with two different scale mills. Cheniere and Cypress were milled with a McGill No. 2 mill and a pilot scale mill (Satake). Both material streams, rice kernels and bran, were collected and weighed. Measurements of Degree of milling, transparency, and whiteness were made with a milling meter (Satake). Yield and bran fraction were calculated. Samples of the bran were heat stabilized and prepared for high pressure liquid chromatography (HPLC). HPLC analysis determined the concentration of vitamin E and oryzanol. Parameter values were reported as laboratory, pilot, or category assignment of low, medium, and high. Yield values for both rice varieties and both mill scales were highest at the low category. Degree of milling measurements increased with increasing process time setting for the laboratory scale mill and with increasing operational mill setting for the pilot scale mill. DOM data divided by category showed an increase for both varieties and both mill scales from the low to high categories. Transparency and whiteness values increased from low to high category. At the laboratory scale mill, for Cheniere, the highest levels of vitamin E and oryzanol occurred at the 10 second mill setting. For Cypress, the highest level of vitamin E occurred at the 10 second mill setting, and the highest level of oryzanol resulted at the 5 second time setting. Category and pilot scale values for both vitamin E and oryzanol were highest at the low category or the lowest mill setting.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".