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Record W2093874888 · doi:10.1039/c3ay41732h

A porous layer open tubular monolith on microstructured optical fibre for microextraction and online GC-MS applications

2014· article· en· W2093874888 on OpenAlexaff
Samuel M. Mugo, Lauren Huybregts, James Mazurok

Bibliographic record

VenueAnalytical Methods · 2014
Typearticle
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsMacEwan University
Fundersnot available
KeywordsSolid-phase microextractionExtraction (chemistry)MonolithMaterials sciencePolymerDivinylbenzenePorosityAnalyteFabricationFiberDetection limitStyreneChromatographyAnalytical Chemistry (journal)Gas chromatography–mass spectrometryChemistryMass spectrometryComposite materialCopolymerOrganic chemistry

Abstract

fetched live from OpenAlex

A microextraction device comprising a porous layer open tubular (PLOT) polymer housed in a microstructured optical fiber has been shown to be an attractive tool for analyte extraction and coupling to GC-MS as a cost-effective alternative to traditional SPME. This paper details the fabrication of a poly(styrene-co-divinylbenzene) PLOT optical fibre microextraction device and its use in the extraction of polyaromatic hydrocarbons (PAHs) in aqueous solution. Good linear calibrations were obtained with R2 values above 0.970 for five PAHs analyzed, with percent relative standard deviation values of 22.2 to 43.6% for PAH standards with concentrations ranging from 0.1 to 100 ppm. In addition, the robust poly(styrene-co-DVB) PLOT optical fibre porous polymer microextraction (PPME) device appears to retain its effectiveness with repeated use over an extended period of time.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.053
GPT teacher head0.408
Teacher spread0.356 · 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 source (direct Gemma or distilled Codex), 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

Citations11
Published2014
Admission routes1
Has abstractyes

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