Automation of Solid-Phase Microextraction-Gas Chromatography-Mass Spectrometry Extraction of Eucalyptus Volatiles
Bibliographic record
Abstract
Solid-phase microextraction (SPME) coupled with gas chromatography (GC)-ion-trap mass spectrometry (ITMS) is employed to analyze fragrance compounds from different species of eucalyptus trees: Eucalyptus dunnii, Eucalyptus saligna, Eucalyptus grandis, and hybrids of other species. The analyses are performed using an automated system for preincubation, extraction, injection, and analysis of samples. The autosampler used is a CombiPAL and has much flexibility for the development of SPME methods and accommodates a variety of vial sizes. For automated fragrance analysis the 10- and 20-mL vials are the most appropriate. The chromatographic separation and identification of the analytes are performed with a Varian Saturn 4D GC-ITMS using an HP-5MS capillary column. Several compounds of eucalyptus volatiles are identified, with good reproducibility for both the peak areas and retention times. Equilibrium extraction provides maximal sensitivity but requires additional consideration for the effect of carryover. Preequilibrium extraction allows good sensitivity with minimal carryover.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 0.001 |
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".