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Record W2907483884 · doi:10.15562/bmj.v7i3.1219

Description of nutritional status and the incidence of stunting children in early childhood education programs in Bali-Indonesia

2018· article· en· W2907483884 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBali Medical Journal · 2018
Typearticle
Languageen
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsUnderweightWastingAnthropometryOverweightEnvironmental healthMedicineIncidence (geometry)Cognitive developmentPediatricsEarly childhoodDemographyGerontologyPsychologyCognitionBody mass indexDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

Introduction: Early childhood is often called the golden age that is an active individual with rapid growth and development so the nutritional needs must be met and balanced. Every parent would want a balance between physical growth and optimal mental development in their child. In reality, there are still some cases of under-nutrition, stunting, and wasting in some areas of Bali Province. This is certainly a challenge for governments, especially health providers to reduce and prevent that situation because the lack of nutrients that occur in this golden period is irreversible. The less nutritional status will decrease the cognitive abilities development, the child easily sick and low competitiveness. This study aims to know the description of the nutritional status and the incidence of stunting children in early childhood in Bali Province.Method: This research was observational with cross-sectional design, involving 53 children in early childhood programs which are scattered in several regencies in Bali Province such as Bangli, Gianyar, Singaraja, and Denpasar. The nutritional status of children was assessed by comparing body weight with age, whereas stunting incidence was evaluated by comparing height with age using an anthropometric standard of child nutritional status assessment based on Minister of Health Decree No. 1995/MENKES/SK/XII/2010.Result: This research showed that 35.85% sample were underweight, 60.38% well nourished, and 3.77% overweight. The data after Height/Age measurement has shown that 9.43% sample were short, 73.58% normal, and 16.98% tall. Conclusion: This study has concluded most of the sample were well nourished (60.38%), nevertheless there was still underweight and overweight sample. According to the Height/Age index can be concluded that most of the sample was normal 73.8%. Also, some of the samples were short and tall.Â

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.044
Threshold uncertainty score0.241

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.017
GPT teacher head0.294
Teacher spread0.277 · 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