MétaCan
Menu
Back to cohort
Record W4406778286 · doi:10.29303/jppi.v4i3.3888

PENDAMPINGAN DAN SOSIALISASI DALAM MEMATUHI PROTOKOL KESEHATAN UPAYA PENCEGAHAN VIRUS CORONA (COVID 19) DI SDK ST. ARNOLDUS, KUPANG

2024· article· id· W4406778286 on OpenAlexaff
Suprabadevi Ayumayasari Saraswati, Lebrina Ivantry Boikh, Azaz Ayubi, Rut Kristiani Huky

Bibliographic record

Venueindonesian journal of fisheries community empowerment · 2024
Typearticle
Languageid
FieldSocial Sciences
TopicCOVID-19 Prevention and Impact
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Corona (planetary geology)ChemistryPhysicsMedicineInternal medicineAstrobiology

Abstract

fetched live from OpenAlex

Pendampingan dan Pendekatan melalui kegiatan pengabdian masyarakat yaitu Pendampingan Dan Sosialisasi Dalam Mematuhi Protokol Kesehatan Upaya Pencegahan Virus Corona (Covid 19) Di Sdk St. Arnoldus, Kupang”. Kegiatan pengabdian masyarakat ini diharapkan dapat menyelesaikan masalah yang terjadi di masyarakat pesisir Kota Kupang melalui pendampingan dan pendekatan persuasif dan mendampingi siswa-siswi dalam menghadapi krisis pandemi Covid 19. Implementasi kebijakan dari pemerintah untuk memperkecil angka penyebaran covid-19 terus dilakukan kepada setiap lapisan masyarakat, termasuk kelompok anak-anak usia dini yang belum sepenuhnya paham akan bahaya dari virus ini. Salah satu upaya pencegahan penyebaran Covid-19 kepada masyarakat khususnya siswa-siswa di Sdk St. Arnoldus, Kupang diharapkan melalui pendampingan ini dilakukan dengan cara mendongeng (story telling) dan sosialisasi protokol Kesehatan tentang cara pencegahan penyebaran Covid-19 demi menyesuaikan tingkat pemahaman siswa-siswa di Sdk St. Arnoldus. Sehingga anak dapat mengerti akan cara pencegahan dan penanggulangan bencana pandemic covid 19 dengan melaksanakan protokol kesehatan.

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)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.740
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0030.003
Open science0.0030.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.076
GPT teacher head0.370
Teacher spread0.294 · 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 designQualitative
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueindonesian journal of fisheries community empowermentSame topicCOVID-19 Prevention and ImpactFrench-language works237,207