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Record W2761847906 · doi:10.1080/0972060x.2017.1377639

Anti-Bacterial Activity of Extract and the Chemical Composition of Essential Oils in <i>Cirsium arvense</i> from Iran

2017· article· en· W2761847906 on OpenAlexaboutno aff
Ali Dehjurian, J. Lari, Alireza Motavalizadehkakhky

Bibliographic record

VenueJournal of Essential Oil Bearing Plants · 2017
Typearticle
Languageen
FieldMedicine
TopicSilymarin and Mushroom Poisoning
Canadian institutionsnot available
Fundersnot available
KeywordsCirsium arvenseThistleEssential oilWeedNoxious weedBotanyBiologyChemical compositionHerbChemistryTraditional medicineMedicinal herbs

Abstract

fetched live from OpenAlex

Cirsium arvense, known as “Kharlateh” or “Kangar Sahraee” in Iran, is a plant classified as an agricultural weed. Canada thistle is the common name for C. arvense. In this study we investigated the chemical composition of the essential oils in C. arvense using GC/Mass spectroscopy. Each of the aerial parts of the plant flower, leaf and stem was investigated separately. Nineteen compounds were detected in the flower part, accounting for 96.5 % of the total oil. The main compounds are α-bisabolol (17.4 %), hexacosane (12.6 %), δ-cadinene (9.7 %). The leaf oils contained 12 compounds (99.7 % of the total oil), of which the three main compounds were α-bisabolol (34.8 %), δ-cadinene (20.7 %) and β-selinene (15.6 %). Twelve components (96.6 %) were also detected in the stem, including α-bisabolol and δ-cadinene, which account for 45.8 % and 23.8 % respectively. We also studied antibacterial activity C. arvense methanolic and hexanoic extracts. The results indicated that the plants hexane and methanol extracts showed antibacterial activities.

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)0.001
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 score0.207
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.019
GPT teacher head0.282
Teacher spread0.263 · 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

Citations9
Published2017
Admission routes1
Has abstractyes

Explore more

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