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Record W2319969336 · doi:10.1093/chromsci/44.6.366

Online Coupling of Solid-Phase Microextraction and Capillary Electrophoresis

2006· article· en· W2319969336 on OpenAlexaff
Zhihong Liu, Janusz Pawliszyn

Bibliographic record

VenueJournal of Chromatographic Science · 2006
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSolid-phase microextractionCapillary electrophoresisChemistryMicroscale chemistryChromatographySample preparationCoupling (piping)Capillary actionAnalytical Chemistry (journal)Mass spectrometryGas chromatography–mass spectrometryMaterials science

Abstract

fetched live from OpenAlex

Solid-phase microextraction (SPME) and capillary electrophoresis (CE) are two of the main inventions that shaped 20th Century analytical chemistry. SPME is an effective microscale sampling and sample preparation technique, and CE is a high-efficiency microanalytical method. Online coupling of SPME with CE can be a powerful combination because of the significant advantages of the two techniques. The progress in the development of online SPME-CE coupling is surveyed in this review. Problems encountered and solutions reported are highlighted.

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)0.002
metaresearch head score (Gemma)0.002
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: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.004

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 head0.005
GPT teacher head0.257
Teacher spread0.251 · 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
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

Citations28
Published2006
Admission routes1
Has abstractyes

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