Microwave-Assisted Headspace Solid-Phase Microextraction for the Analysis of Bioemissions from<i>Eucalyptus citriodora</i>Leaves
Bibliographic record
Abstract
Microwave-assisted headspace solid-phase microextraction (MA-HS-SPME) was developed as a simple and effective method for fast sampling of volatile organic compounds (VOCs) from Eucalyptus citriodora Hook (E. citriodora) leaves. During microwave heating, a simple shielding device made of aluminum foil was used to protect the SPME fiber from microwave irradiation while allowing the sample to be heated. A room temperature water bath was also used to allow microwave heating to be conducted in a more controlled manner. The inner heating caused by microwave irradiation dramatically accelerated the emission of VOCs from the sample, but no marked change in headspace temperature in the sample vial was found. Under optimum conditions, the extraction efficiencies obtained with microwave heating were much higher than those obtained without microwave heating for all fibers used, namely, 7-microm polydimethylsiloxane (PDMS), 100-microm polydimethylsiloxane (PDMS), 65-microm polydimethylsiloxane/divinylbenzene (PDMS/DVB), and 75-microm carboxen/polydimethylsiloxane (CAR/PDMS). The improvement of extraction efficiency using MA-HS-SPME allowed more VOC events to be detected, with more balanced extraction of VOCs of lower and higher molecular masses. Moreover, a good linear relationship was found between sample size and GC-FID response (total peak area of VOCs), indicating the usefulness of MA-HS-SPME for quantitative analysis of individual volatile compounds in E. citriodora leaves.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 teacher head, 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".