MétaCan
Menu
Back to cohort
Record W4396879428 · doi:10.62817/jkbl.v16i1.282

HUBUNGAN STATUS KELENGKAPAN IMUNISASI DASAR DENGAN KEJADIAN STUNTING PADA USIA ANAK 24 - 59 BULAN

2023· article· id· W4396879428 on OpenAlexaff
Ujang Daud, Ijun Rijwan Susanto, Karwati

Bibliographic record

VenueJurnal Kesehatan Budi Luhur · 2023
Typearticle
Languageid
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

Masalah malnutrisi yang mendapat banyak perhatian akhir-akhir ini adalah masalah kurang gizi kronis dalam bentuk anak pendek atau stunting. Stunting merupakan keadaan status gizi dimana panjang badan atau tinggi badan menurut umur di bawah standar yang dijadikan parameter. Permasalahan gizi kurang yang dialami dalam waktu lama pada masa pertumbuhan dan perkembangan dari awal kehidupan dapat menunjukkan masalah stunting. Penelitian ini bertujuan untuk mengetahui hubungan status kelengkapan imunisasi dasar dengan kejadian stunting pada anak usia 24 - 59 bulan di wilayah kerja puskesmas Cimahi Selatan kota Cimahi. Rancangan penelitian yang penulis gunakan dalam penelitian ini adalah rancangan penelitian survey analitik jenis Case Control Retropektif. Sampel minimum untuk penelitian ini adalah 41 sampel. Rasio kasus dan kontrol adalah 1:1. Jadi, total sampel menjadi 82 responden, yang terdiri dari 41 kasus dan 41 kontrol. Hasil uji statistik menunujukan nilai p-value 0,208 (> α0,05) berarti dapat disimpulkan tidak terdapat hubungan antara Status Kelengkapan Imunisasi Dasar Dengan Kejadian Stunting Pada Anak Usia 24 - 59 Bulan Di Wilayah Kerja Puskesmas Cimahi Selatan Kota Cimahi. Stunting berpeluang 1,562 kali (95% CI: 0,123 - 1,618) pada balita yang melakukan imunisasi tidak lengkap dibandungkan dengan imunisasi lengkap. Kata kunci: Stunting, Imunisasi Dasar Anak, Malnutrisi Anak

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.003

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 head0.044
GPT teacher head0.322
Teacher spread0.278 · 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.

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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJurnal Kesehatan Budi LuhurSame topicPublic Health and NutritionFrench-language works237,207