Home fortification with micronutrient sprinkles – A new approach for the prevention and treatment of nutritional anemias
Bibliographic record
Abstract
Despite global goals set by United Nations' agencies over the past decade for significant reductions in iron deficiency anemia (IDA), it remains a largely unaddressed public health problem affecting more than two billion people, one-third of the world's population. The negative impact of IDA on health and human potential are greatest in the developing world, where it is estimated that 51% of children younger than four years of age are anemic, mainly due to a diet that is inadequate in bioavailable iron. Studies in both developed and developing countries have consistently shown mental and motor impairments that may not be reversible in children younger than two years of age with IDA. From a public health standpoint there are four possible interventions for the prevention of anemia: dietary diversification to include foods rich in absorbable iron; fortification of staple foods including targeted fortification of complementary foods for infants and young children; the provision of iron supplements; and 'home-fortification'. In response to a United Nations Children's Fund (UNICEF) request to develop a new approach to IDA, our research group developed 'Sprinkles' for home-fortification of complementary foods. Sprinkles are single-dose sachets (like small packets of sugar) containing micronutrients in powder form (encapsulated iron, zinc, vitamins A, C and D, and folic acid), which are easily sprinkled onto any home-prepared complementary food. Sprinkles were developed to overcome many of the side effects and disadvantages of iron drops. We have demonstrated that Sprinkles are as effective as iron drops in the treatment and prevention of anemia. Sprinkles are easier to use and are, therefore, better accepted than iron drops, which may improve adherence to iron interventions.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Overview of micronutrient Sprinkles for home fortification against iron deficiency anemia; the object is a nutrition intervention.
The work concerns micronutrient treatment for anemia, not research practice.
Public-health intervention for nutritional anemia via micronutrient sprinkles; clinical/public-health object.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".