Adaptation of a compact rapid vitamin A assay device (iCHECK™) to simulated field conditions and relevant substrates in Guatemala
Bibliographic record
Abstract
Background Guatemala has mandated fortifying granulated table sugar with vitamin A at 10–20 ppm. Children in the interior commonly continue partial breast‐feeding through the first 2 y of life. Objective To adapt the preparation of samples of sugar and bovine milk for a rapid assessment of vitamin A using nonlaboratory items for mixing and measuring. Methods Sugar samples were mixed for homogenization in plastic bags, with 4 g delivered into a 20 mL syringe to prepare a 20 w/v% solution. Heavy cream was diluted in plastic bags. Samples were injected into iEX™ extraction vials and measured by fluorometry in an iCHECK™(BioAnalyt, Telbow, Germany) rapid assay unit, providing digital read‐outs in μ/L. Results Intra‐sample CVs ranged from 0.3–7.8% and intraobserver CVs ranged from 2.1– 15.0% for dairy. The r value for the inter‐observer assay association for 12 sugar specimens was 0.86 (p<0.001). Inter‐observer accord on median vitamin A values was excellent for both substrates. Plausible values for sugar vitamin A, with a median of 11 ppm, were found for 58 samples of sugar gathered from across 4 regions. Conclusion The iCHECK™ system provides plausible values for vitamin A content of fortified sugar and bovine milk and cream. It offers important promise for a rapid, on‐site, field‐level evaluation of materials for timely public health responses. Supported by a donation from Sight & Life
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".