Ethnopharmacology and Antioxidant Activity Studies of Woody Liana Original Wallacea
Bibliographic record
Abstract
Lore Lindu National Park is a habitat located in the middle of the Wallacea Region, consisting of various types of medicinal plants, including lianas. This area is surrounded by the Kaili Tribe, which possesses adequate ethnopharmacology knowledge and local wisdom in managing living natural resources. Studies on the medicinal plant species of lianas original Wallacea have not been conducted. Therefore, this study aims to reveal Kaili’s ethnopharmacology of woody liana plants and identify the metabolic content and antioxidant activity. This study was carried out at the Lore Lindu National Park with the purposive and snowball sampling methods used to determine the respondents. Furthermore, the Harborne and 2,2-diphenyl-1-picrylhydrazyl (DPPH) methods were used to analyze the phytochemical content and antioxidant activities. The results showed that the Kaili people used the lianas Poikilospermum suaveolens (Blume) Merr, Arcangelisia Flava (L.) Merr, Fibrauea Tinctoria Lour, and Maclura cochinchinensis (Lour.) Corner are medicine for treating various types of chronic diseases. The plant's bark and wood are used as medicine by processing boiled/brewed hot water, or by pounded, and smeared over the wound. The phytochemical analysis results showed that alkaloids are contained in all types of lianas, while flavonoids and tannins are found only in 3 types. Meanwhile, the P. suaveolens contained saponin, A. flava bark extract has potential to be developed as an antioxidant.
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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) | 0.002 | 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".