Bibliographic record
Abstract
Vitamin D deficiency is widely prevalent in India, despite abundant sunshine. Fortification of staple foods with vitamin D is a viable strategy to target an entire population. Vitamin D fortification programs implemented in the United States and Canada have improved the vitamin D status in these countries, but a significant proportion of the population is still vitamin D deficient. Before fortification programs are designed and implemented in India, it is necessary to study the efficacy of the American and Canadian vitamin D fortification programs and then improve upon them to suit the Indian scenario. This review explores potential strategies that could be used for the fortification of foods in the Indian context. These strategies have been proposed considering the diverse dietary practices necessitated by social, economic, cultural and religious practices and the diverse climatic conditions in India. Fortification of staple foods, such as chapati flour, maida, rice flour and rice, may be more viable strategies. Targeted fortification strategies to meet the special nutritional needs of children in India are discussed separately in a review entitled, "Fortification of foods with vitamin D in India: Strategies targeted at children".
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".