Bibliographic record
Abstract
The present study was conducted to evaluate the ethno-veterinary medicinal plants traditionally used for curing of animals in district Charsadda.Farmers in most of the villages in District Charsadda treat the animals using local plants and because of poverty, they do not depend on English medicines.Survey was carried out and information was collected from local peoples that most of them were formers.Questionnaires were asked from 40 informants of various villages.A total of 60 plants belonging from total 34 families were collected from district that local people use for Ethnoveterinary purpose (EVP).Most commonly used parts of ethnoveterinary plants are Fruits 14 (8.4%), leaf and seeds 12 (7.2%),Whole plant 6 (3.6%), bark 4 (2.4%),Rhizome 3 (1.8%),Flower, bulb, oil and latex 2 each of one is (1.2%) and stem are 1 (1.6%).It was also observed that old people from age of 75-80 have most knowledge about the ethnoveterinary plants.Solanaceae is the highest family in the study area involved in curing of different ethnoveterinary medicines' preparations.It was also observed that skin diseases are common in the area followed by weakness, diarrhea, shortage of milk and death during birth is very rare in District Charsadda.
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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 | 0.000 | 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) | 0.987 | 0.942 |
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; both teacher heads agree on what is shown here.
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".