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Determinan Akses Sumber Air Minum Layak di Provinsi Bengkulu Tahun 2021

2022· article· id· W4309695857 on OpenAlexaff
Monica Putri, Aisyah Fitri Yuniasih

Bibliographic record

VenueSeminar Nasional Official Statistics · 2022
Typearticle
Languageid
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsPhysics

Abstract

fetched live from OpenAlex

Air minum yang aman dan layak merupakan elemen penting dalam mewujudkan kehidupan yang sehat. Selama periode 2017-2021, Provinsi Bengkulu menjadi provinsi dengan rata-rata persentase akses air sumber minum layak terendah di Indonesia. Pada tahun 2021, persentase akses sumber air minum layak di Provinsi Bengkulu masih di bawah nasional yaitu sebesar 67,39 persen. Angka ini masih belum bisa mencapai target RPJMN untuk mencapai akses air minum layak sebesar 100 persen. Tujuan dari penelitian ini adalah menganalisis gambar umum dan menganalisis variabel yang memengaruhi beserta kecenderungan mengenai akses sumber air minum layak di Provinsi Bengkulu tahun 2021 dengan metode analisis regresi logistik biner multilevel. Hasil dari penelitian ini menunjukkan bahwa variabel pada level rumah tangga yaitu klasifkasi daerah, fasilitas sanitasi, pendidikan KRT dan status kemiskinan berpengaruh signifikan terhadap akses sumber air minum layak. Kemudian variabel di level wilayah yaitu PDRB per kapita juga berpengaruh signifikan terhadap akses sumber air minum layak

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)0.001
metaresearch head score (Gemma)0.002
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.289
Teacher spread0.273 · 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 designNot applicable
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

Citations2
Published2022
Admission routes1
Has abstractyes

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