Medicinal and Aromatic Plants Diversity in Greece and Their Future Prospects: A Review
Bibliographic record
Abstract
The Mediterranean, a biodiversity hotspot, is rich in medicinal and aromatic plants covering an extensive area with different environmental conditions. The geographical position of Greece, its geomorphology, the presence of flora of past geological eras and the coexistence and interplay of biotic and non biotic factors have defined it as a region of high plant diversity and endemism, a fact that also impacts the category of medicinal and aromatic plants (MAPs). The past 30 years there has been a rapid growth of interest in MAPs as a result of the vital contributions these goods make to large numbers of rural communities. At the same time there is a shift within many developing countries from subsistence to commercial usage. MAPs are important factors in sustainable development, environmental protection and public health. In Greece, they are expected to play an important role in the country’s agricultural profile due to quantitative and qualitative advantages. MAP cultivation can help small-scale farmers strengthen their livelihoods and as a result, greater access to a wider range of assets can be achieved, and a capacity to build these into successful and sustainable activities. This review aims at profiling the current state of MAP cultivation in Greece, as well as their future sustainability prospects.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".