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Record W2329702961 · doi:10.1021/ac301305u

Optimization of Fiber Coating Structure Enables Direct Immersion Solid Phase Microextraction and High-Throughput Determination of Complex Samples

2012· article· en· W2329702961 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnalytical Chemistry · 2012
Typearticle
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSolid-phase microextractionChemistryCoatingChromatographyFiberExtraction (chemistry)DesorptionAdsorptionGas chromatography–mass spectrometryMass spectrometryOrganic chemistry

Abstract

fetched live from OpenAlex

This study presents a new approach for improving the structure, and hence the robustness, of the SPME fiber coating applied for gas chromatography (GC) analysis. It involves application of an external layer of poly(dimethyl siloxane) (PDMS) over the commercial PDMS/divinyl benzene (DVB) extraction phase. The fiber provided extraction capabilities similar to that exhibited by the original PDMS/DVB fiber toward triazole pesticides from water samples. Furthermore, the fiber could be utilized for over 100 extractions in direct contact with a complex food matrix such as whole grape pulp, with no sample pretreatment required. The amount of extracted pesticides from whole grape pulp had RSD values below 20% throughout 130 extraction/desorption/conditioning cycles, which is a dramatic improvement when compared to commercial PDMS/DVB fiber coating applied in food analysis facilitating high-throughput automation.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0050.000

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 head0.036
GPT teacher head0.336
Teacher spread0.300 · 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