Pengembangan Potensi Spatial Dan Aspatial Desa Bone-Bone Sebagai Destinasi Wellness Tourism
Bibliographic record
Abstract
Abstract. This research aims to explain and map the spatial and aspatial potential of Bone-Bone Village which supports the development of wellness tourism and to test the influence of spatial and aspatial potential on the development of health tourism. This research uses mixed methods as consideration and reference material for descriptive analysis. This research uses qualitative descriptive analysis to find out what spatial and aspatial potential Bone-Bone Village has that supports wellness tourism and path analysis to test how spatial and aspatial potential influences the development of wellness tourism. Abstrak. Penelitian ini bertujuan untuk menjelaskan dan memetakan potensi spatial dan aspatial yang dimiliki Desa Bone-Bone yang mendukung pengembangan wellness tourism serta menguji pengaruh potensi spatial dan aspatial terhadap pengembangan wellness tourism. Penelitian ini adalah mixed methods sebagai bahan pertimbangan serta bahan rujukan dalam menganalisis secara deskriptif. Penelitian ini menggunakan analisis deskriptif kualitatif untuk mengetahui apa saja potensi spatial dan aspatil yang dimiliki Desa Bone-Bone yang mendukung wellness tourism dan analisis jalur (path analysis) untuk menguji bagaimana pengaruh potensi spatial dan aspatial terhadap pengembangan wellness tourism.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.000 |
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".