Thiamine fortification strategies in low‐ and middle‐income settings: a review
Bibliographic record
Abstract
) is an essential micronutrient in energy metabolism and cognitive and neurological health. Thiamine deficiency disorders (TDDs) have a range of clinical presentations that result in various morbidities and can be fatal if not promptly recognized and treated, especially in infants. To intervene, thiamine intakes by breastfeeding mothers and others at risk of thiamine deficiency should be increased to ensure adequate thiamine intake. Although thiamine fortification programs have a long history in high-income countries, there are few mandatory fortification programs to address TDDs in low- and middle-income countries (LMICs), particularly in the regions of greatest concern, South and Southeast Asia. This review highlights essential aspects for consideration in the development of a mandatory fortification program in LMICs, including an overview of the data required to model fortification dosing schemes, available thiamine fortificants, and potential fortification vehicles, as well as identifies current knowledge gaps.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".