MétaCan
Menu
Back to cohort
Record W2997414094 · doi:10.24036/abdi.v1i2.11

Pelatihan Teknik Pengumpulan Data Geografis Berbantuan Peta dan Citra pada Siswa SMA

2019· article· id· W2997414094 on OpenAlex

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

VenueAbdi Jurnal Pengabdian dan Pemberdayaan Masyarakat · 2019
Typearticle
Languageid
FieldSocial Sciences
TopicSTEM Education
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Pembelajaran penelitian-penelitian geografi merupakan salah satu goal pendidikan dalam Kurikulum 2013. Kompetensi yang harus dicapai siswa dalam materi ini adalah memahami langkah-langkah penelitian geografi, termasuk teknik-teknik pengumpulan data geografis. Karena itu, diperlukan pelatihan bagi siswa yang bertujuan untuk meningkatkan kemampuan siswa dalam memahami teknik pengumpulan data geografis. Kegiatan pelatihan menggunakan media peta dan citra. Luaran utama yang diharapkan dalam pengabdian ini adalah jurnal atau publikasi ilmiah. Mitra kegiatan pengabdian ini adalah siswa SMA YPK Diaspora Kotaraja dengan lokasi kegiatan di sekolah dan Kawasan Pantai Base-G, Kota Jayapura. Metode pelaksanaan kegiatan pengabdian dalam bentuk pelatihan. Kegiatan pelatihan dilaksanakan dalam bentuk pemberian materi, praktek interpretasi peta dan citra. Hasil kegiatan pengabdian menunjukkan bahwa siswa peserta pelatihan telah mampu mengumpulkan data geografis melalui interpretasi peta dan citra.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, 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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.327
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.003
Science and technology studies0.0030.002
Scholarly communication0.0020.004
Open science0.0070.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.009

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 head0.036
GPT teacher head0.302
Teacher spread0.266 · 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