Solid-Phase Microextraction of Volatile Compounds from the Chopped Leaves of Three Species of <i>Eucalyptus</i>
Bibliographic record
Abstract
Headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography and ion-trap mass spectrometry has been used to identify biogenic volatile organic compounds present in the headspace of chopped leaves of Eucalyptus (E.) dunnii, E. citriodora, and E. saligna. A simple HS-SPME method entailing 30 min of extraction at 30 degrees C was developed for this purpose. Thirty compounds were identified in the headspace of 60 juvenile chopped Eucalyptus leaves, and another 30 were tentatively identified. The presence of compounds such as (E)-4,8-dimethyl-1,3,7-nonatriene (DMNT), (E,E)-4,8,12-trimethyl-1,3,7,11-tridecatetraene (TMNT), (E,E)-alpha-farnesene, (E,E,E)-3,7,11,15-tetramethyl-1,3,6,10,14-hexadecapentaene (TMHP), beta-caryophyllene, alpha-humulene, germacrene D, and beta-cubebene in the headspace of the leaves but not in the essential oils from the same Eucalyptus trees and information about the infochemical roles of some of these compounds in other living plant systems suggest they might play a bioactive role in Eucalyptus leaves.
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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".