Medicinal Plants Used in Folk Recipes by the Inhabitants of Himalayan Region Poonch Valley Azad Kashmir (Pakistan)
Bibliographic record
Abstract
Plants with medicinal properties were held in the highest esteem in indigenous medicine systems all over the world. All indigenous remedies, whether traditional or modern, have originated directly or indirectly from folklore, rituals and folk medicinal knowledge. The objective of this study was to collect the information about how the local people used the plants of their area to cure a wide variety of ailments in human and livestock. Extensive surveys were carried out during the field work; interviews were conducted with the local inhabitants, the herbalists ‘Hakims’ (local physicians). About fifty informants were interviewed on random basis. The ethnobotanical data obtained was checked and compared with the existing literature and was analysed both qualitatively and quantitatively. In total 68 species of plants belonging to 44 families were recorded as used medicinally for preparations of folk recipes of 68 ailments. During the field study, it was found that the indigenous knowledge related to medicinal uses comes from women age between 30-50 years, whereas the folk medicinal use comes from men. This survey indicated that 72% source of indigenous knowledge related to the medicinal use of plants comes from people between age of 50 years, while 28% of it comes from people between age 30 and 50 years. The survey also indicated that men especially old one’s are more informative of folk knowledge of medicinal plants than women in the area. It was also indicated that about 60% of the homemade drugs were used by people above the age of 50 years, 30% by children below age of 15 years especially infants. While remaining 10% of the traditional medicines of plant origin were utilized by people between ages of 15-50 years.
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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 | 0.001 |
| 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".