MétaCan
Menu
Back to cohort
Record W1506602450 · doi:10.1002/jssc.201500158

Evaluation of a multi‐fiber exchange solid‐phase microextraction system and its application to on‐site sampling

2015· article· en· W1506602450 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Separation Science · 2015
Typearticle
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSolid-phase microextractionFiberChromatographyEthylbenzeneMaterials scienceChemistryProcess engineeringTolueneGas chromatography–mass spectrometryMass spectrometryComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Until recently, multiple solid-phase microextraction fibers could not be automatically desorbed in a single gas chromatographic sequence without manual intervention from an operator. This drawback had been a critical issue, particularly during the analysis of numerous on-site samples taken with various fiber assemblies. Recently, a Multi-Fiber Exchange system, designed to overcome this flaw found in other commercially available autosamplers, was released. In the current research, a critical evaluation of the Multi-Fiber Exchange system performance in terms of storage stability and long-term operation is presented. It was established in the course of our research that the Multi-Fiber Exchange system can operate continuously and precisely for multiple extraction/injection cycles. However, when the effect of residence time of commercial fibers on the Multi-Fiber Exchange tray was evaluated, results showed that among the evaluated fiber coatings, Carboxen/polydimethylsiloxane was the only coating capable of efficient storage on the tray for up to 24 h after field sampling without suffering significant loss of analytes (≤10% for benzene, toluene, ethylbenzene, o-xylene, decane, and limonene). Additionally, the system capability for high-throughput analysis was demonstrated by the unattended desorption of multiple fibers after on-site sampling of toluene, indoor air levels, in a polymer synthesis lab.

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)0.006
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 score0.212
Threshold uncertainty score0.319

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
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)0.0000.000

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 head0.216
GPT teacher head0.497
Teacher spread0.282 · 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