Diversity Status and Sustainable Uses of Some Minor Forest Products in Ban Thung Soong Community Forest in Krabi Province, Thailand
Bibliographic record
Abstract
The diversity status and sustainable uses of some Minor Forest Products in Ban Thung Soong Community Forest in Krabi Province were evaluated based on Important Value Index (IVI) analysis, utilizing method and quantitative ecological data based on local wisdom. The studies were found that at the highest level of 200-300 m altitude, the number of trees and total basal area was the highest than at level elevations of 0-100 m and 100-200 m from 12 stands (20x50 m2/stand). From IVI analysis, there were 65 species of plants found in Ban Thung Soong Community Forest (BTSCF). Analysis of IVI were found that the Xylia xylocarpa (Roxb.) Taub. var. kerrii (Craib & Hutch.) I.C.Nielsen shows the highest IVI with 22.37%. The highest percentage of relative density, relative frequencies and relative dominance were found in Homalium undulatum King with 7.50%, and 7.55% with Xylia xylocarpa (Roxb.) Taub. var. kerrii (Craib & Hutch.) I.C.Nielsen respectively. The numbers of species in BTSCF were 49+65 species ha-1 and comprises of number of trees, saplings and seedlings ha-1 were 4,697; 119,166 and 252,500 of trees ha-1 respectively. There were 49 species categorized as Minor Forest Products (MFPs) which include medicinal plants, edible plants, and non-edible plants.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".