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Record W4313562303 · doi:10.25047/j-kes.v10i3.359

Faktor Ibu Dan Anak Pada Kejadian Stunting Di Puskesmas Batakte

2022· article· id· W4313562303 on OpenAlexaff
Amelya B. Sir, Simplexius Asa, Indriati Tedjuhinga, Imelda F. E. Manurung, Dwi Windoe, Ampera Wadu

Bibliographic record

VenueJurnal Kesehatan · 2022
Typearticle
Languageid
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsMedicineGynecology

Abstract

fetched live from OpenAlex

Balita stunting memiliki risiko penurunan kemampuan intelektual, produktivitas, dan peningkatan penyakit degeneratif di masa mendatang. Hasil Riskesdas 2018 menunjukkan bahwa Nusa Tenggara Timur merupakan provinsi dengan proporsi balita gizi pendek dan sangat pendek tertinggi, yaitu 42,4%. Tujuan penelitian untuk menganalisis faktor risiko stunting pada anak balita di wilayah kerja Puskesmas Batakte Kabupaten Kupang. Rancangan penelitian ini adalah studi kasus kontrol. Subjek penelitian adalah balita usia (0-59 bulan) dengan kelompok kasus balita stunting sedangkan sampel kontrol adalah balita normal dengan perbandingan 1:1 sebanyak 48 balita dan ibu balita sebagai responden. Pemilihan sampel menggunakan simple random sampling. Analisis data menggunakan uji chi-square dan perhitungan OR untuk menilai faktor risiko. Penelitian dilaksanakan di wilayah kerja Puskesmas Batakte pada bulan Agustus sampai Oktober 2021. Variabel penelitian adalah riwayat penyakit menular, berat badan lahir rendah, pendidikan ibu, pola asuh, usia pekerjaan ibu saat hamil dan usia kehamilan. Hasil penelitian menunjukkan ada hubungan antara riwayat penyakit menular (OR=5.000; 95% CI 1.165-21.459), berat badan lahir rendah (BBLR) (OR=5.909; 95% CI 1.546-22.580), pendidikan ibu (OR=4,491; 95% CI 1,260-16,006) dan pola asuh (OR=6,000; 95% CI 1,711-21,038) dengan stunting pada anak balita, sedangkan pekerjaan ibu, usia saat hamil dan usia kehamilan tidak berhubungan dengan stunting pada anak balita di wilayah kerja Puskesmas Batakte.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.502
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.027
GPT teacher head0.294
Teacher spread0.267 · 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
Published2022
Admission routes1
Has abstractyes

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