Fortification of condiments with micronutrients in public health: from proof of concept to scaling up
Bibliographic record
Abstract
Fortification of condiments or seasonings may be useful for delivering micronutrients if they are consumed consistently by most of the population, as occurs in many countries. The World Health Organization, in collaboration with the Micronutrient Initiative and the Sackler Institute for Nutrition Science at the New York Academy of Sciences, convened a technical consultation on "Fortification of Condiments and Seasonings with Vitamins and Minerals in Public Health: from Proof of Concept to Scaling Up" to review the role of condiments and seasonings in improving micronutrient status, as constituents of regular diets and patterns of production and consumption worldwide. The consultation covered aspects related to implementation, monitoring, evaluation, and legal frameworks of fortification programs, as well as food safety and policy coherence for condiment fortification in the context of other public health strategies. This paper introduces the background and rationale of the technical consultation, synopsizes the presentations, and provides a summary of the main considerations proposed by the working groups.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".