Ethnobotanical Study of Medicinal Plants Used as Therapeutic Agents to Manage Diseases of Humans
Bibliographic record
Abstract
Objective. This work aimed to survey medicinal plants used in phytotherapy in the Fez-Boulemane region, Morocco. Methods. A comprehensive ethnobotanical survey was conducted using a questionnaire to collect data from thirty herbalists on medicinal plants used for therapeutic purposes in the Fez-Boulemane region, Morocco. Results. The mean age of herbalists interviewed was 52.13 years. Forty percent of the herbalists were illiterate, and 73% referred to the experiences of their parents as knowledge of the properties and uses of medicinal plants. One hundred and eight medicinal plants belonging to 51 botanical families were recommended by herbalists in the region of Fez-Boulemane, Morocco, for treatment. According to the respondents, Lawsonia inermis L., Rosmarinus officinalis L., and Lavandula coronopifolia L. were the most used plants with the percentage of 13%, 12%, and 11%, respectively. Most plants had been involved in the treatment of digestive disorders (25%) and osteoarticular diseases (24%). Some (7.4%) of the plants mentioned in our survey were potentially toxic. Conclusion. It was learned that irrational use of toxic plants and unknown compositions of recipes are recommended to consumers. As a result, particular attention should be paid to risks related to plants used in traditional treatment without scientific validation. It is envisaged that increasing awareness, by conducting educational campaigns and transferring evidence-based scientific knowledge, on traditional treatments among the local population is expected to have beneficial impacts on health and disease management.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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 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".