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Record W4413115616 · doi:10.1136/bmjgh-2024-017228

Infants and children 6–59 months of age with moderate wasting: evidence gaps identified during WHO guideline development

2025· article· en· W4413115616 on OpenAlexaff
Indi Trehan, Robert Bandsma, Bindi Borg, Mary Christine Castro, Kate Golden, Debbie Thompson, Michael McCaul, Celeste Naude, Jaden Bendabenda, Kirrily de Polnay, Zita Weise Prinzo, Allison I Daniel

Bibliographic record

VenueBMJ Global Health · 2025
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersChildren's Investment Fund FoundationWorld Health Organization
KeywordsWastingGuidelineMedicinePediatricsInternal medicinePathology

Abstract

fetched live from OpenAlex

More than two-thirds of wasted children worldwide have moderate wasting, accounting for no less than 30 million children at any given time in 2024, most of whom reside in South Asia, SouthEast Asia and sub-Saharan Africa. 1 This population of infants and children 6–59 months old is defined by having a mid-upper-arm circumference (a measure of lean body mass) between 115 and less than 125 mm and/or a weight-for-height between 2 and 3 SDs below the median defined by the 2006 WHO Child Growth Standards.2 While those with moderate wasting have a significantly lower mortality rate than those with severe wasting or nutritional oedema, their much larger population means that they still account for approximately 30%–40% of the deaths due to wasting.3

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)0.021
metaresearch head score (Gemma)0.087
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.038
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.087
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0040.004
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.024
GPT teacher head0.366
Teacher spread0.342 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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