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Record W2099459756 · doi:10.1039/b617355a

Equilibrium in-fiber standardization method for determination of sample volume by solid phase microextraction

2007· article· en· W2099459756 on OpenAlexaff
Vadoud Niri, Janusz Pawliszyn

Bibliographic record

VenueThe Analyst · 2007
Typearticle
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSolid-phase microextractionChromatographyFiberChemistryVolume (thermodynamics)Analytical Chemistry (journal)Standard solutionStandard additionWineMass spectrometryGas chromatographySample (material)Sample preparationGas chromatography–mass spectrometryDetection limitThermodynamics

Abstract

fetched live from OpenAlex

This paper describes an in-fiber standardization method by Solid Phase Microextraction (SPME) for the determination of a sample volume. After loading a specific amount of standard, the volumetric standard, on a PDMS-coated fiber (n(0)), the fiber was exposed in the headspace of sample vials containing different volumes of water. The amount of standard that remained on the fiber after equilibrium (n(f)), which was determined with gas chromatography/mass spectrometry (GC/MS), depends on the volume of the sample. Naphthalene, 1-methylnaphthalene, 2-methylnaphthalene, 1-ethylnaphthalene, and 2-ethylnaphthalene were chosen as volumetric standards based on theoretical calculations. The effect of loading time, exposure time, and exposure temperature were investigated. The effect of the matrix was also studied, analyzing both water and wine samples. Precision and accuracy of the method were obtained for each standard in both water and wine. The partition coefficients of the compounds between the fiber and the sample (K(fs)) and between the headspace and the sample (K(hs)) were obtained by plotting n(0)/n(f)versus sample volume.

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)0.002
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: Methods · Consensus signal: none
Teacher disagreement score0.501
Threshold uncertainty score0.622

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.025
GPT teacher head0.393
Teacher spread0.368 · 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
GenreMethods

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

Citations8
Published2007
Admission routes1
Has abstractyes

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