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Record W4254201194 · doi:10.25311/keskom.vol2.iss4.63

Hubungan Pemberian Makanan Pendamping Asi Dini dengan Status Gizi Bayi 0-11 Bulan di Puskesmas Bangko Rokan Hilir

2014· article· id· W4254201194 on OpenAlexaff
Winda Septiani

Bibliographic record

VenueJurnal kesehatan komunitas (Journal of community health) · 2014
Typearticle
Languageid
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsMedicineGynecology

Abstract

fetched live from OpenAlex

Masalah dalam penelitian ini adalah masih rendahnya persentase ASI eksklusif dan tingginya persentase pemberian MP-ASI dini pada bayi 0-11 bulan di Kelurahan Bagan Barat Wilayah Kerja Puskesmas Bangko Rokan Hilir. Penelitian ini bertujuan untuk mengetahui hubungan pemberian MP-ASI dini dengan status gizi bayi 0-11 bulan di Kelurahan Bagan Barat Wilayah Kerja Puskesmas Bangko Rokan Hilir. Jenis penelitian adalah kuantitatif dengan jenis disain penelitian cross sectional. Dilaksanakan di Kelurahan Bagan Barat Wilayah Kerja Puskesmas Bangko Rokan Hilir dari tanggal 20 Mei hingga 20 Juni 2011, dengan jumlah sampel 67 responden yang diambil dengan menggunakan teknik Proporsional Random Sampling. Pengumpulan data dilakukan dengan metode wawancara menggunakan kuesioner dan analisis yang digunakan adalah univariat, bivariat duiji dengan uji chi-square dan multivariate diuji dengan uji regression logistic ganda. Hasil penelitian ini didapatkan bahwa prevalensi gizi kurang sebesar 31,1%. Rata-rata umur pemberian MP-ASI dini < 6 bulan sebesar 59,7%. Dari hasil analisis multivariate didapatkan adanya hubungan yang bermakna antara pemberian MP-ASI dini dengan status gizi bayi 0-11 bulan. Bayi yang diberi MP-ASI < 6 bulan mempunyai peluang bayinya berstatus gizi tidak normal 16,694 kali dibandingkan dengan bayi yang diberi MP-ASI ≥ 6 bulan setelah dikontrol oleh pendidikan, pengetahuan dan pekerjaan

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)0.020
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.189
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0030.002
Science and technology studies0.0050.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.014
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 head0.040
GPT teacher head0.337
Teacher spread0.298 · 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; both teacher heads agree on what is shown here.

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

Citations10
Published2014
Admission routes1
Has abstractyes

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