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Record W4388597378 · doi:10.1111/mcn.13575

Sensory evaluations of a novel iron and zinc‐enriched powder for the potential treatment and prevention of iron deficiency in women of reproductive age

2023· article· en· W4388597378 on OpenAlexaff
Clara H. Miller, Hauna Sheyholislami, Jessie L. Burns, Kristin L. Connor

Bibliographic record

VenueMaternal and Child Nutrition · 2023
Typearticle
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsCarleton University
Fundersnot available
KeywordsMedicineZincIron deficiencyPhysiologySensory systemInternal medicineMetallurgyAnemiaNeuroscience

Abstract

fetched live from OpenAlex

Iron deficiency (ID) and ID with anaemia (IDA) are serious global health problems that disproportionately affect women aged 15-49 years. Although food fortification is one of the most effective and sustainable ways to combat nutritional deficiencies, iron remains one of the most difficult micronutrients to fortify, given its tendency to react strongly with food constituents. Therefore, it is important to assess the sensory properties of foods fortified with iron to determine the acceptability and palatability in target populations. We aimed to determine the palatability and acceptability of a novel iron and zinc-enriched powder fortified in tap water by conducting sensory evaluations in 35 women of reproductive age using a 9-point hedonic scale, where participants rated the sensory properties of six samples containing different amounts of the active or placebo powder. We found significant differences between samples reconstituted at 1, 2, and 3 g/L for sensory properties, including overall taste. Participants were found to be more willing to drink the mineral-enriched powder when prepared at the lowest concentration (1 g/L) compared to higher concentrations. Our results provide important insight into the sensory qualities of a novel formulation of an iron and zinc-enriched powder for at-home fortification and indicate consumer acceptability in reproductive-aged women, a key group at risk for ID/IDA. If found to improve iron status, novel treatments like this product will contribute to global efforts to develop safe, acceptable and sustainable interventions for ID and IDA.

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 score0.948
Threshold uncertainty score0.159

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 head0.019
GPT teacher head0.287
Teacher spread0.268 · 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

Citations7
Published2023
Admission routes1
Has abstractyes

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