Ethnobotanical Studies of Medicinal Plants used to Treat Human and Livestock Ailments in Southern Nations, Nationalities and Peoples’ Region, Ethiopia: A Systematic Review
Bibliographic record
Abstract
Like many other parts of Ethiopia, people in the Southern Nations, Nationalities and Peoples’ Region (SNNPR) do have indigenous knowledge on the preparation and use of traditional medicinal plants. Even though different studies have been conducted to document medicinal plants in different zones of SNNPR separately, there is no previous review work which summarizes the medicinal plants and the associated indigenous knowledge at the regional level (at SNNPR region as a whole or in large scale). Also, there is no previous review work that prioritizes the factors that affect medicinal plants at the regional level (including threatened medicinal plants). The purpose of this paper was to review habitat, growth forms, the method of remedy preparation and administration, marketability of medicinal plants, and to prioritize the factors that affect medicinal plants in SNNPR. Most of the medicinal plants in the majority of the reviewed areas are harvested from wild. Herbs are the most utilized life forms and leaves are the most utilized plant part in the preparation of remedies. Fresh plant materials are the most employed in the preparation of remedies. Majority of medicinal plants are not marketable. Agricultural land expansion is a major threat to medicinal plants which followed by deforestation. Olea europaea subsp. cuspidata, Prunus africana, Echinops kebericho, Croton macrostachys, Cordia africana and Dodonaea angustifolia, Hagenia abyssinica, Withania somnifera and Ficus spp are the highly affected medicinal plant species which require conservation and management priority in the region.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 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 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".