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Record W4392161181 · doi:10.1080/09637486.2024.2314676

Dietary aflatoxins exposure, environmental enteropathy, and their relation with childhood stunting

2024· article· en· W4392161181 on OpenAlexaff
Markos Makiso Urugo, Tilahun A. Teka, Tefera Belachew, Janerose Nasimiyu Lusweti, Jasmina Djedjibegovíc, Carl Lachat, Kokeb Tesfamariam, Addisalem Mesfin, Tess Astatkie, Mosaad A. Abdel‐Wahhab

Bibliographic record

VenueInternational Journal of Food Sciences and Nutrition · 2024
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsDalhousie University
Fundersnot available
KeywordsAflatoxinEnvironmental healthEnteropathyFood scienceMedicineBiologyInternal medicineDisease

Abstract

fetched live from OpenAlex

, during breastfeeding, and consumption of contaminated food affect the gut microbiome, resulting in intestinal dysfunction and potentially contributing to stunting. This review explores the potential relationship between AF exposure, environmental enteropathy and childhood stunting. AFs bind to DNA, disrupt protein synthesis and elicit environmental enteropathy (EE). An EE alters the structure of intestinal epithelial cells, impairs nutrient uptake and leads to malabsorption. This article proposes possible intervention strategies for researchers and policymakers to reduce AF exposure, EE and childhood stunting, such as exposure reduction, the implementation of good agricultural practices, dietary diversification and improving environmental water sanitation and hygiene.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.241
Teacher spread0.229 · 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 source (direct Gemma or distilled Codex), 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

Citations9
Published2024
Admission routes1
Has abstractyes

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