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Record W101918276 · doi:10.1177/156482650402500306

Stability of Salt Double-Fortified with Ferrous Fumarate and Potassium Iodate Or Iodide under Storage and Distribution Conditions in Kenya

2004· article· en· W101918276 on OpenAlexaff
Toks Oshinowo, Levente L. Diósady, Rizwan Yusufali, Louis Laleye

Bibliographic record

VenueFood and Nutrition Bulletin · 2004
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsNutrition InternationalUniversity of Toronto
FundersUNICEF
KeywordsIodinePotassium iodateIodised saltFerrousChemistrySalt (chemistry)IodatePotassiumIodideMoistureIodine deficiencyInorganic chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The stability of table salt double-fortified with iron as ferrous fumarate, and with iodine as potassium iodide or potassium iodate, has been investigated under actual field conditions of storage and distribution in the coastal and highland regions of Kenya. Seven 200-g sample packets of double-fortified salt in sealed polyethylene bags and a similar packet containing a datalogger for monitoring temperature and humidity were packaged with 21 sample bags of salt from another study into a bundle, which then entered the distribution network from a salt manufacturer's facility to the consumer. Iodine retention values of up to 90% or more were obtained during the three-month study. Double-fortified salt was prepared using ferrous fumarate microencapsulated with a combination of binders and coloring agents and coated with soy stearine, in combination with either iodated salt or salt iodized with potassium iodide microencapsulated with dextrin and coated with soy stearine. Most of the ferrous iron was retained, with less than 17% being oxidized to the ferric state. The polyethylene film overwrap of salt packs in the bundles provided significant protection from ambient humidity. Salt double-fortified with iodine and microencapsulated iron ferrous fumarate premix was generally quite stable, because both iodine and ferrous iron were protected during distribution and retail in typical tropical conditions in Kenya's highlands and humid lowlands.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score0.614

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.255
Teacher spread0.233 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations26
Published2004
Admission routes1
Has abstractyes

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