Stability of Vitamin A in Bolivian Fortified Cooking Oil
Bibliographic record
Abstract
Fortification of a commonly consumed food is often an effective and relatively inexpensive method to alleviate the problem of human vitamin A deficiency. However, among the problems associated with food fortification, stability of the nutrient in the food vehicle must be considered. We tested stability of vitamin A (retinyl palmitate) in commercially available fortified cooking oil from Bolivia under parameters of storage time, temperature and humidity, and light exposure, in both opaque and translucent original containers. Containers of fortified soybean oil were incubated for 36 weeks in chambers maintained at either 40C (75% relative humidity) or 25C (60% relative humidity), at light intensity 2400 lux. At intervals, samples were withdrawn and analyzed by HPLC. All samples showed similar concentrations of vitamin A (32 to 50 ug retinyl palmitate per mL oil) at the beginning of the trial. After 4 weeks (maximum commercial turnover time of the oil), vitamin A content of the samples in translucent containers had decreased to 21% (25C) or 9% (40C) of initial values; however, samples in opaque containers retained 62 to 68% of initial vitamin A. Samples in opaque containers retained 62% (at 25C) or 50% (at 40C) of vitamin A for 17 weeks of treatment.
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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 | 0.000 | 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) | 0.001 | 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".