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Record W4221001755 · doi:10.3390/plants11070951

Chemical Profile and Antimicrobial Activity of the Essential Oils of Helichrysum arenarium (L.) Moench. and Helichrysum italicum (Roth.) G. Don

2022· article· en· W4221001755 on OpenAlexaff
Valtcho D. Zheljazkov, İvanka Semerdjıeva, Еlina Yankova-Tsvetkova, Tess Astatkie, Stanko Stanev, Ivayla Dincheva, Miroslava Kačániová

Bibliographic record

VenuePlants · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEssential Oils and Antimicrobial Activity
Canadian institutionsDalhousie University
Fundersnot available
KeywordsSabineneLimoneneBotanyPopulationChemistryChemical compositionTraditional medicineBiologyEssential oilOrganic chemistry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.269

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.187
Teacher spread0.179 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations27
Published2022
Admission routes1
Has abstractyes

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