Chemical Profile and Antimicrobial Activity of the Essential Oils of Helichrysum arenarium (L.) Moench. and Helichrysum italicum (Roth.) G. Don
Bibliographic record
Abstract
This study compared the essential oils (EO) composition of Helichrysum arenarium (Bulgarian populations) with that of the cultivated species H. italicum. The EO composition of H. arenarium and H. italicum were analyzed via gas chromatography. In general, 75 components were identified in H. arenarium EO and 79 in H. italicum EO. The predominant constituents in H. arenarium EO were α-pinene (34.64–44.35%) and sabinene (10.63–11.1%), which affirmed the examined population as a new chemical type. Overall, the main EO constituents of H. italicum originating in France, Bosnia and Corsica were neryl acetate (4.04–14.87%) and β-himachalene (9.9–10.99%). However, the EOs profile of H. italicum introduced from the above three countries differed to some extent. D-limonene (5.23%), italicene, α-guaiene and neryl acetate (14.87%) predominated in the H. italicum introduced from France, while α-pinene (13.74%), δ-cadinene (5.51%), α-cadinene (3.3%), β-caryophyllene (3.65%) and α-calacorene (1.63%) predominated in plants introduced from Bosnia. The EOs of the plants introduced from France and Corsica had similar chemical composition and antimicrobiological activity.
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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) | 0.000 | 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".