Optimization of vitamins A and D3 loading in re-assembled casein micelles and effect of loading on stability of vitamin D3 during storage
Bibliographic record
Abstract
The objectives of this study were to apply response surface methodology to optimize fat-soluble vitamin loading in re-assembled casein micelles, and to evaluate vitamin D stability of dry formulations during ambient or accelerated storage and in fortified fluid skim milk stored under refrigeration. Optimal loading of vitamin A (1.46-1.48mg/100mgcasein) was found at 9.7mM phosphate, 5.5mM citrate and 30.0mM calcium, while optimal loading of vitamin D (1.38-1.46mg/100mg casein) was found at 4.9mM phosphate, 4.0mM citrate and 26.1mM calcium. In general, more vitamin D was retained in vitamin D-re-assembled casein micelles than control powders during storage, while vitamin D loss was not different for vitamin D-re-assembled casein micelles and control fortified milks after 21days of refrigerated storage with light exposure. In conclusion, re-assembled casein micelles with high loading efficiency show promise for improving vitamin D stability during dry storage.
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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 | 0.001 | 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 | 0.000 | 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".