Screening of Phytoresources from the Romanian Flora with medical applications against Covid - Review
Bibliographic record
Abstract
Plants are an important means of combating numerous harmful influences on humans (microorganisms, viruses, fungi, etc.) and have always been used to treat various diseases. In the context of the Covid pandemic, interest in the use of plants has increased. Great importance has been given to screening plants' potential against Covid (antiviral, anti-inflammatory, immunostimulatory, and antioxidant). According to recent research, many of the plant species used against Covid are of Asian origin. In this review, we aim to discuss the plant species with these medicinal potentials with a focus on Romanian flora. We have listed a total of 50 Phyto-resources from Romanian flora with different potentials: 26 containing the confirmed anti-covid compounds, and 9 species having antiviral, anti-inflammatory, immunostimulant, and antioxidant potentials.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".