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Record W4391750180 · doi:10.24036/abdi.v5i4.516

Usaha Peningkatan Kesehatan dan Pencegahan Penularan Covid-19 Melalui Program PIS-PK Berbasis Sumber Daya Lokal di Wilayah Kerja Puskesmas Nanggalo Kota Padang

2023· article· id· W4391750180 on OpenAlexaff
Lola Felnanda Amri, Murniati Muchtar, Yosi Suryarinilsih, Delima Delima, Yessi Fadriyanti, Asep Irfan

Bibliographic record

VenueAbdi Jurnal Pengabdian dan Pemberdayaan Masyarakat · 2023
Typearticle
Languageid
FieldHealth Professions
TopicHealthcare Quality and Satisfaction
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

Covid-19 dan persiapan new normal berakibat menjadi penurunan pada derajat kesehatan masayarakat. Tujuan dilakukan kegiatan pengabdian masyarakat diharapkan dapat pemecahan masalah PIS_PK melalui partisipasi masyarakat dengan pengembangan potensi dan sumber daya lokal dalam mencapai kelurahan sehat di masa new normal. model pemberdayaan yang akan dilakukan dalam pengabdian masyarakat ini adalah model pengembangan lokal yaitu pemberdayaan masyarakat sehingga akan terjadinya peningkatan pada pengetahuan, sikap dan tindakan masyarakat setelah dilakukan intervensi. Pelaksanaan kegiatan pada pengabdian masyarakat ini dilakukan dalam beberapa tahapan yaitu, tahap persiapan/pendataan awal, tahap pelaksanaan, dan tahap evaluasi. Strategi pelaksanaan kegiatan yang dilakukan beruba survei lokasi pengabdian masyarakat pada Kelurahan terpadat serta angka kesakitan tinggi akibat prilaku dan kesadaran akan kesehatan yang masih kurang. Kemudian memberikan Sasaran pelayanan kesehatan pada masyakarakat yang memenuhi kriteria, yaitu Pelayanan kesehatan meliputi identifikasi kasus dengan melakukan edukasi dan pendampingan, serta pemanfaatan potensi lokal dalam pembuatan cuci tangan.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.085
Threshold uncertainty score0.283

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0850.021

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 head0.120
GPT teacher head0.440
Teacher spread0.320 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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