The Potency of Cratoxylum arborescens Blume (Geronggang) and Combrecarpus rotundatus Dans (Tumih) as Natural Regeneration in Degraded Tropical Peat Swamp Forest
Bibliographic record
Abstract
The massive forest fire disasters have left an enormous area of degraded peatland. This study aims to analyze the performance of two species, namely C. arborescens and C. rotundatus, as the natural regeneration post forest fires. This research was conducted in 5 different locations that experienced severe fires in 2006. We made a total of 25 plots for each location to measure biodiversity at four growth levels. We analyzed the data with vegetation analysis formulas from Magurran. The results show that at the tree growth level, C. rotundatus can withstand the fires in 2006 and is currently still growing in more significant numbers than C. arborescens. At the pole, sapling, and seedling growth levels, these species perform well as natural regeneration species with many individuals, but C. arborescens is a bit more dominant. Both species are suitable for natural regeneration after fires in degraded peat swamp forests based on survived and existing individuals. On the other hand, both species could not improve the vegetation diversity in the whole ecosystem. These two species can be the option for natural regeneration if there a limited budget and the degraded areas are in a very remote location.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 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".