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Record W4385561113 · doi:10.59737/jpmpi.v1i1.19

Kegiatan Screening Menggunakan Aplikasi dan Pemberian Vaksinasi Sinovac Pada ASN di DIY untuk Pencegahan Covid-19

2021· article· id· W4385561113 on OpenAlexaff
Dwi Ratnaningsih

Bibliographic record

VenueJurnal Pengabdian Masyarakat Permata Indonesia · 2021
Typearticle
Languageid
FieldSocial Sciences
TopicCOVID-19 Prevention and Impact
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsMedicineCoronavirus disease 2019 (COVID-19)GynecologyVirologyInternal medicineInfectious disease (medical specialty)Disease

Abstract

fetched live from OpenAlex

Hingga kini pandemic virus Corona belum juga berakhir. Guna menekan kasus yang terus bertambah, pemberian vaksin COVID-19 mulai dilakukan. Pemerintah pun menganjurkan agar semua orang mendapatkannya. Saat ini, vaksin COVID-19 tengah didistribusikan ke seluruh masyarakat Indonesia. Pemberian vaksin ini merupakan solusi yang dianggap paling tepat untuk mengurangi jumlah kasus infeksi virus SARS-CoV-2 penyebab penyakit COVID-19. Tujuan yang ingin dicapai dengan pemberian vaksin COVID-19 adalah menurunnya angka kesakitan dan angka kematian akibat virus ini. Meskipun tidak 100% bisa melindungi seseorang dari infeksi virus Corona, vaksin ini dapat memperkecil kemungkinan terjadinya gejala yang berat dan komplikasi akibat COVID-19. Selain itu, vaksinasi COVID-19 bertujuan untuk mendorong terbentuknya herd immunity atau kekebalan kelompok. Hal ini penting karena ada sebagian orang yang tidak bisa divaksin karena alasan tertentu., misalnya diabetes atau hipertensi yang tidak terkontrol. Kegiatan PPM ini dilaksanakan pada hari pada hari Rabu, 17 Maret 2021 di Joga Expo Centre (JEC). Peserta dalam kegiatan ini adalah seluruh ASN yang berada di Wilayah Kota Yogyakarta. Kegiatan ini berjalan dengan baik dan berhasil. Hal ini di tunjukkan dengan sikap antusia semua peserta dalam melakukan vaksinasi berjalan dengan lancar

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)0.004
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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.530
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.004
Science and technology studies0.0060.001
Scholarly communication0.0040.003
Open science0.0030.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.052
GPT teacher head0.345
Teacher spread0.293 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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