MétaCan
Menu
Back to cohort
Record W3198959964 · doi:10.23887/jwl.v10i2.38369

PELATIHAN PEMANFAATAN CYBER COUNSELING BERBASIS MOBILE UNTUK MEMAKSIMALKAN KOMPETENSI SISWA MAGANG DI SMKN BALI MANDARA

2021· article· id· W3198959964 on OpenAlex
Agus Aan Jiwa Permana, Made Putrama, Komang Setemen

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJURNAL WIDYA LAKSANA · 2021
Typearticle
Languageid
FieldComputer Science
TopicBlockchain Technology in Education and Learning
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsHumanitiesPsychologyArt

Abstract

fetched live from OpenAlex

Salah satu sekolah vokasi yang intens dalam mencetak lulusan dengan target 70% lulusan bekerja di Industri adalah SMKN Bali Mandara. Melalui komunikasi langsung dengan Bapak I Wayan Agustiana, S.Pd., M.Pd selaku Kepala Sekolah dan Wakasek serta Guru di SMKN Bali Mandara mengatakan hal yang sama yaitu minimal 70% siswanya ditargetkan bekerja. Permasalahan yang dihadapi oleh mitra yang merupakan sekolah vokasi ini adalah bagaimana cara membentuk karakter siswa selain memiliki kecerdasan interpersonal juga memiliki kompetensi yang unggul. Melalui pengabdian tahun 2020, pengabdi sudah melaksanakan pelatihan kepada tim guru dan staff di SMKN Bali Mandara untuk melakukan seleksi siswa baru menggunakan tes online bernama Simaju Ganesha. Melalui kerjasama dengan pihak sekolah, pelatihan bertujuan memperkenalkan aplikasi mobile. Adapun peserta yang megikuti adalah guru dan siswa kelas XII yang akan magang. Hasilnya pelatihan berupa (1) pedoman user manual software, (2) hasil tes software lokasi yang sesuai dengan minat siswa

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.767
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.010
GPT teacher head0.255
Teacher spread0.245 · 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