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Record W3113459817 · doi:10.1002/elps.202000239

Electrospray ionization stability and concentration sensitivity in capillary electrophoresis‐mass spectrometry using a flow‐through microvial interface

2020· article· en· W3113459817 on OpenAlexafffund
Lingyu Wang, Yueyang Li, Dazhou Chen, David D. Y. Chen

Bibliographic record

VenueElectrophoresis · 2020
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMass spectrometryAnalytical Chemistry (journal)Electrospray ionizationElectrosprayChemistryCapillary electrophoresisCapillary electrophoresis–mass spectrometryDetection limitReproducibilityChromatographyCommon emitterCapillary actionVolumetric flow rateMaterials scienceOptoelectronics

Abstract

fetched live from OpenAlex

Concentration sensitivity is a key performance indicator for analytical techniques including for capillary electrophoresis-mass spectrometry (CE-MS) with electrospray ionization (ESI). In this study, a flow-through microvial interface was used to couple CE with MS and improve the ESI stability and detection sensitivity. By infusing a peptide mixture through the interface into an MS detector at a typical flow rate for CE-MS analysis, the spatial region near the interface was mapped for MS signal intensity. When the sprayer tip was within a 6 × 6.5 × 5 mm region in front of the MS inlet, the ESI was stable with no significant loss of signal intensity for ions with m/z 239. Finite element simulations showed that the average electric field strength at the emitter tip did not change significantly with minor changes in emitter tip location. Experiments were conducted with four different mass spectrometer platforms coupled to CE via the flow-through microvial interface. Key performance indicators, that is, limit of detection (LOD) and linearity of calibration curves were measured for nine amino acids and five peptides. Inter- and intraday reproducibility were also tested. The results were shown to be suitable for quantification when internal standards were used.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.139
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.211
Teacher spread0.201 · 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.

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

Citations9
Published2020
Admission routes2
Has abstractyes

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