Quality Criteria for Micronutrient Powder Products: Report of a Meeting Organized by the World Food Programme and Sprinkles Global Health Initiative
Bibliographic record
Abstract
Distribution of micronutrient powder (MNP), also known as Sprinkles", is becoming a preferred strategy for addressing micronutrient deficiencies. In response, different formulations are being developed, different producers manufacture MNP and several organizations coordinate distribution. However, as yet, the supply of MNP as well as experience with large-scale MNP programs is limited. To facilitate expansion of MNP use such that acceptability and compliance are high and effectiveness maintained, product quality, of both powder and packaging, good advocacy among decision makers, and providing good information to the target population are crucial. A meeting was organized in Toronto by the Sprinkles Global Health Initiative and the World Food Programme to review and reach consensus on quality criteria for composition, manufacturing, packaging, and labeling of MNP propose guidelines for wide-scale production, and discuss MNP program experience. It was recognized that the durability of some of the more sensitive micronutrients in their powdered form in the harsh climatic conditions of many countries has implications for formulation, packaging, storage, and handling of the MNP product. A question-and-answer manual would greatly facilitate program design and implementation. It was agreed to form an interim Technical Advisory Group to prepare for formation of a Technical Advisory Group with agreed-upon tasks and responsibilities. The MNP manufacturing manual of the Sprinkles Global Health Initiative can continue to be used, with reference to the recommendations from the Toronto Meeting outlined in this paper. Meanwhile, the Sprinkles Global Health Initiative will not place any encumbrances on production using its manual; however, the brand name Sprinkles" will stay protected under various trademark laws.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.054 | 0.015 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".