Optimalisasi Pemanfaatan Ruang Berbasis Kebijakan Berkelanjutan di Hutan Mangrove Kabupaten Wakatobi
Bibliographic record
Abstract
Selain terkenal dengan panorama bawah laut yang langsung dirasakan masyarakat, Wakatobi juga memiliki persebaran mangrove yang cukup luas, terutama di Pulau Kaledupa dan di banyak tempat lainnya. Keberadaan potensi mangrove yang sangat besar ini harus ditelaah lebih lanjut, terutama dalam hal penataan ruang, yang mencakup kebijakan berkelanjutan, yang diharapkan berdampak positif terhadap aspek lingkungan, sosial, dan ekonomi masyarakat. Hamparan vegetasi mangrove di Kabupaten Wakatobi harus dilihat sebagai potensi yang selain dapat dimanfaatkan untuk pemanfaatan alam bawah laut juga dapat memberikan nilai ekonomi bagi masyarakat dan nilai tambah bagi pemerintah daerah. Konservasi mangrove juga harus mampu memberikan timbal balik finansial sehingga konsep berkelanjutan dapat diterapkan untuk mencapai tujuan pengelolaan berkelanjutan. Optimalisasi ruang melalui kebijakan berkelanjutan hutan mangrove di Kabupaten Wakatobi diperlukan untuk memaksimalkan perannya sebagai penyangga lingkungan pesisir dan memberikan manfaat ekonomi bagi masyarakat sekitar.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".