Penentuan Analisa Tapak Secara Makro, Messo dan Mikro Dalam Proses Penetapan Tapak.
Bibliographic record
Abstract
Desa Wisata adalah gagasan desa mandiri yang tanggap terhadap potensi desa dan minat wisatawan. Desa Mangliawan yang terletak di kabupaten Malang memiliki potensi wisata desa berupa destinasi Taman Wisata Taman Sangaloh. Namun Potensi ini tidak di iringi oleh ketersediaanya fasilitator pendamping dalam pengembangan desa wisata ini. Berbekal dari latar belakang tersebut desa Mangliawan membutuhkan sebuah gagasan metode pendekatan sosial yang berbasis masyarakat yang dapat memberikan kontribusi gagasan melalui forum diskusi, FGD maupun bentuk metode pendekatan sosial yang lain dalam pengembangan desa Mangliawan khususnya Kawasan wisata taman Sengaloh. Penentuan Analisa Tapak secara Makro, Messo dan mikro adalaha salah satu proses metode pendekatan yang digunakan fasilitator dalam mendampingi desa. Pada ulasan literatur ini, di dapatkan metode penetapan Analisa tapak dengan data primer dan sekunder melaui FGD (Focus Grup Discussion).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.006 |
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".