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Correlation Between Diet History and Nutritional Status of Children Aged 24–59 Months in Tarumajaya, Bekasi in 2019

2024· article· en· W4402323694 on OpenAlexaff
Lailan Safina Nasution, Nursakinah A. Karim

Bibliographic record

VenueJurnal Gizi dan Pangan · 2024
Typearticle
Languageen
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsCorrelationEnvironmental healthPsychologyGerontologyDemographyMedicineMathematicsSociology

Abstract

fetched live from OpenAlex

This study aimed to analyze the correlation between diet history and the nutritional status of pre-school children. This was an analytical observational study using a cross-sectional design. Sam-ples were 96 children aged 24‒59 months in Tarumajaya, Bekasi, West Java. Diet history was obtained from questionnaires containing history of breastfeeding and diet since the infancy period. The children’s heights were measured using a microtoise stature meter. Subjects were considered stunted if their Height-for-Age Z-score was minus 2 or lower according to WHO Child Growth Standard. Data was analyzed using Fisher’s exact test. Out of the 96 children, 16 (16.7%) were stunted. There were 80 (83.3%) children who received exclusive breastfeeding, 51 (53.1%) who received an appropriate frequency of meals, 78 (81.3%) who met the minimum dietary diversity, and 29 (30.2%) who had a minimum acceptable diet. Fisher’s exact test showed that dietary diversity was a significant factor for stunted children (p<0.001).

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: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.274
Teacher spread0.256 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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