KEANEKARAGAMAN VEGETASI ULTRABASA DI HUTAN LINDUNG NANGA-NANGA PAPALIA KOTA KENDARI
Bibliographic record
Abstract
This research aimed to determine the ultra-basic vegetation diversity in the Nanga-Nanga Papalia Protected Forest, Kendari City, Southeast Sulawesi. The study was conducted in May to June 2023, covering an area of 42 hectares within the Nanga-Nanga Papalia Protected Forest. The sampling intensity was set at 5% over a study area of 2.1 hectares, resulting in 52 sampling plots arranged using the Line Transect method. The findings revealed that the ultra-basic vegetation diversity across all vegetation levels in the protected forest was classified as low, with values of 1.25 for trees, 1.22 for saplings, 1.27 for poles, and 1.13 for seedlings
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".