Bibliographic record
Abstract
The study was conducted for ethnobotanical study of district Karak for a period of one year during 2014-2015.The study indicated that the inhabitants of District Karak utilized 45 plant species, 21 herbs, 12 shrubs and 12 trees, for four ethnobotanical categories including fuel, fodder, medicinal and mechanical uses.Some useful species were collected near human settlements regardless the diversity of species at distant area.The main threats to plant are anthropogenic activities.The general presence of herbs and shrubs species in semi-arid zone reduces the mechanical uses of the plants.Otherwise, most of the trees would have been mostly used as a mechanical source such as timber purpose.However, increasing education, awareness of the people due to the service in Government institutions, the notion of the sustainable use of resources is rising among the people of the area.This sustainable uses will conserve and preserve natural resources and biodiversity.Over grazing, commercial timber cutting and in some cases lack of individual ownership were the reasons of unsustainable exploitation of natural resources while pluralism in medicinal system, partial decrease in timber exploitation as income or household source due to more reliability on bricks, concretes and T-Iron for the roof of the houses etc. were the positive signals for preservation and distribution of the local flora which were observed in the area.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.889 | 0.849 |
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; the direct Gemma label and the distilled Codex classifier 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".