Bibliographic record
Abstract
In this Master's thesis we studied whether the extracts of the three goldenrod (Solidago) species have antifungal activity. Since the common goldenrod (S. virgaurea) is indigenous, and the other two – Canadian goldenrod (S. canadensis) and giant goldenrod (S. gigantea) are invasive alien species, we tested the differences in antifungal activity according to their origin and used plant material (leafs, inflorescence) and way of preparing extracts (aqueous, organic – 96 % ethanol). Fungi used in the study were: Alternaria alternata, Alternaria infectoria, Aspergillus flavus, Aureobasidium pullulans, Botrytis cynerea, Epicoccum nigrum, Fusarium poae and Penicillium palitans. We selected these species because of their negative effects on plants grown for food. After one week we measured the area of fungal mycelium and calculated the growth percentage according to the control. We found out that inhibition of fungal growth was similar when aqueous and organic extracts were applied. Also leaf extract caused similar effects as inflorescence extracts. According to the sensitivity to the extracts, the fungi followed the order: F. poae being the most sensitive, than E. nigurm, A. alternata, C. botrytis, A. pullulans, A. infectoria and P. palitans as the least sensitive. The differences in efficiency of the extracts of the leaf and inflorescence extracts of three goldenrod species were not significant.
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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 | 0.000 | 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 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".