MétaCan
Menu
Back to cohort
Record W2085907873 · doi:10.1021/jf0346105

Microwave-Assisted Headspace Solid-Phase Microextraction for the Analysis of Bioemissions from<i>Eucalyptus citriodora</i>Leaves

2003· article· en· W2085907873 on OpenAlexaff
Guohua Xiong, Carolyn Goodridge, Limei Wang, Yong Chen, Janusz Pawliszyn

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2003
Typearticle
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPolydimethylsiloxaneSolid-phase microextractionExtraction (chemistry)ChromatographyDivinylbenzeneMicrowaveSample preparationMaterials scienceAnalytical Chemistry (journal)ChemistryGas chromatography–mass spectrometryMass spectrometryComposite materialStyrenePolymer

Abstract

fetched live from OpenAlex

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.

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)0.001
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 score0.007
Threshold uncertainty score0.665

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.030
GPT teacher head0.314
Teacher spread0.283 · 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

Citations19
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Agricultural and Food ChemistrySame topicAnalytical chemistry methods developmentFrench-language works237,207