Diversity of Rattan Species in Production Forest in Central Sulawesi, Indonesia
Bibliographic record
Abstract
This study aims to explain the diversity of rattan species from production forests in Central Sulawesi. Data collection was carried out with a strip random sampling scheme, in which the sampled strips were 20 x 100 m. Our observation revealed that in the production forest area in Parigi Moutong and Sigi Regencies about 17 species of rattan were identified, which were divided into two genera, each with 14 species of Calamus and 3 species of Daemonorops. The distribution of eleven species was uniform, the distribution of four species was not uniform, and three species had a clumped distribution. The importance of each species varies. There are 8 species with a relatively high mean importance value: Calamus zollingerii (36.62), Calamus ornatus var. celebicus Becc. (24.62), Calamus oodersianus Becc. (23.56), Calamus ornatus var. celebicus Becc. (lambang) (23.49), Calamus didymocarpus (Mart) Becc. (22.99), Calamus inops Becc. (22.25), Calamus sp. (sambuta) (18.00), and Calamus lejocaulis Becc. (15.82), while C. minahassae (dato) has the lowest importance value (6.05). It disclosed, the number of species and distribution of rattan in the production forest of the Central Sulawesi are relatively high and varies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".