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Record W4293071144 · doi:10.1155/2022/7812022

Predicting the Stability of Double Fortified Salt by Determining the Coating Quality of the Encapsulated Iron Premix

2022· article· en· W4293071144 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Food Quality · 2022
Typearticle
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsUniversity of Toronto
FundersBill and Melinda Gates Foundation
KeywordsFortificationSalt (chemistry)ChemistryCoatingFood fortificationIodineFortified FoodFood scienceMicronutrientOrganic chemistry

Abstract

fetched live from OpenAlex

The technology to simultaneously fortify salt with iron and iodine was developed in Canada and transferred and scaled up in India. The double fortified salt has reached more than 60 million consumers so far. Double fortification of salt is a cost-effective and reliable means of improving iron and iodine deficiencies at a population level. However, high-quality iron premix is essential for the stability of iodine and the program’s success. Therefore, we developed a reliable and cost-effective method for premix coating quality evaluation in the field, especially in low-income settings. The integrity and chemical composition of the coating and exposure of iron at the surface (∼10 μm deep) were determined using scanning electron microscopy and energy-dispersive X-ray spectroscopy to predict the stability of the fortified salt. The phenanthroline colour dropper test was used to test the quality of the double fortified salt by reaction with ferrous iron present on the premix surface. Five iron premix samples were compared. Based on the iron release, coating composition, and the reaction with phenanthroline, Premix-3, and its corresponding DFS, obtained from a local shop in India had the lowest quality among all samples tested. The results of the dropper test corresponded with the analysis using sophisticated analytical tools, confirming it as a simple, reliable, and cost-effective test for iron premix coating quality and integrity. This simple test would be crucial for a successful double fortification program, especially in low-income countries, in predicting iron premix quality, a critical determinant of iodine stability during storage, distribution, and retail. These study results can help governments and NGOs to establish quality standards for iron premix used for salt fortification programs.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.385

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.071
GPT teacher head0.340
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it