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Record W3187581857 · doi:10.33846/ghs5407

HUBUNGAN TINGKAT PENGETAHUAN DAN SIKAP PENGAWAS MENELAN OBAT (PMO) DENGAN KEPATUHAN PASIEN TB PARU DI WILAYAH KERJA PUSKESMAS PERAWATAN KAIRATU

2020· article· id· W3187581857 on OpenAlexaff
Wiwi Rumaolat, Maryam Lihi Lihi, Siti Nur Atika Rengur, Sri Mulyati Tunny

Bibliographic record

VenueGLOBAL HEALTH SCIENCE (GHS) · 2020
Typearticle
Languageid
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsGynecologyMedicine

Abstract

fetched live from OpenAlex

Tuberkulosis (TB) Paru sebagai suatu problema kesehatan masyarakat yang sangat penting dan serius untuk ditangani terutama di provinsi maluku yang dari tahun ke tahunnya selalu mengalami peningkatan angka penderita TB Paru. Tujuan penelitian ini untuk mengetahui hubungan tingkat pengetahuan dan sikap PMO dengan kepatuhan pasien TB Paru di Wilayah Kerja Puskesmas Perawatan Kairatu. Desain penelitian ini bersifat deskriktif analitik dengan pendekatan cross sectional. Hasil uji menunjukan adanya hubungan tingkat pengetahuan dan sikap pengawas menelan obat dengan kepatuhan pasien tb paru di wilayah kerja puskesmas perawatan kairatu. ini diperkuat dengan hasil uji statistik chi-square dimana koefisien phi dengan nilai p-value = 0.001 (

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0150.001

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 head0.045
GPT teacher head0.362
Teacher spread0.317 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2020
Admission routes1
Has abstractyes

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