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Record W3011297851 · doi:10.33143/jhtm.v5i2.442

FAKTOR-FAKTOR YANG BERHUBUNGAN DENGAN PEMANFAATAN POSYANDU LANSIA DI WILAYAH PUSKESMAS KUTA ALAM KOTA BANDA ACEH

2019· article· id· W3011297851 on OpenAlexaff
Evi Kurniawati, Siti Hasanah

Bibliographic record

VenueJOURNAL OF HEALTHCARE TECHNOLOGY AND MEDICINE · 2019
Typearticle
Languageid
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsMedicineEnvironmental healthGynecology

Abstract

fetched live from OpenAlex

Besarnya populasi dan pertumbuhan lanjut usia dapat menimbulkan berbagai permasalahan, sehingga perlu pembentukan posyandu lansia. Tujuan penelitian ini untuk mengetahui faktor yang berhubungan dengan pemanfaatan posyandu lansia di wilayah kerja Puskesmas Kuta Alam Banda Aceh tahun 2019. Metode penelitian bersifat analitik, dengan pendekatan Cross Sectional, tehnik pengambilan sampel secara Accidental Sampling, sampel 100 lansia usia >60 tahun. Data diolah dengan analisa univariat dan bivariat. Hasil penelitian, faktor yang berhubungan dengan pemanfaatan posyandu lansia adalah pengetahuan (0,000), dukungan keluarga (0,001). Kesimpulan terdapat hubungan antara pengetahuan dan dukungan keluarga dengan pemanfaatan posyandu lansia. Diharapkan petugas kesehatan meningkatkan sosialisasi pemanfaatan posyandu lansia.

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)0.001
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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0120.002

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 head0.014
GPT teacher head0.313
Teacher spread0.299 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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