PENGEMBANGAN AGROWISATA SUBAK GULINGAN DI KECAMATAN MENGWI KABUPATEN BADUNG
Bibliographic record
Abstract
Pengabdian yang bertujuan untuk mengembangkan agrowisata subak di Desa Gulingan Kecamatan Mengwi Kabupaten badung. Kegiatan yang dilakukan meliputi persiapan, operasional dan evaluasi. Kegiatan persiapan terdiri dari rekrutmen peserta KKN, kordinasi dengan mitra, pembekalan mahasiswa hingga mobilisasi mahasiswa ke lokasi. Kegiatan operasional meliputi: (1) Penataan jalan subak menjadi jalur tracking bagi wisatawan menikmati alam persawahan dan atraksi wisata aktivitas subak; (2) Penguatan kelembagaan subak menjadi pengola daya tarik agrowisata dan pelatihan tenaga pemandu; (3) Pengembangan aktivitas subak menjadi atraksi wisata; (5) Pelatihan pengolahan hasil pertanian dan ikan sebagai hidangan untuk wisatawan bagi wanita tani. Kegiatan evaluasi dilakukan secara berkelanjutan terhadap kemajuan yang diperoleh.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".