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Record W2090982877 · doi:10.1039/c0lc00326c

Radial sample preconcentration

2011· article· en· W2090982877 on OpenAlexafffund
Brent Scarff, Carlos Escobedo, David Sinton

Bibliographic record

VenueLab on a Chip · 2011
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsVictoria UniversityUniversity of Victoria
KeywordsSpark plugMicrofluidicsElectrokinetic phenomenaNanoporousMaterials scienceRotational symmetryConcentration polarizationBuffer (optical fiber)Analytical Chemistry (journal)ChromatographyMechanicsChemistryNanotechnologyEngineeringMechanical engineeringPhysicsElectrical engineering

Abstract

fetched live from OpenAlex

In this paper we present a radial sample preconcentration strategy enabled by axisymmetric concentration polarization in a microfluidic chamber on a uniform nanoporous film. Sample analytes are focused into the centre, creating a concentrated plug that is injected vertically into the microfluidic analysis layer. No balancing pressure driven flows or tangential fields are required, and the process has essentially zero footprint on the analysis layer. An electrokinetic loading scheme enables repeat loading/concentration cycles, and a finned radial chamber geometry dampens instabilities and accommodates larger volumes. Modelling results indicate over 1800-fold concentration increases are possible in 10 s, for high mobility buffers and high applied field strength. At moderate field strength and buffer mobility, experiments demonstrate a 168-fold increase in concentration of FITC-BSA protein in 36 s.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.015
GPT teacher head0.192
Teacher spread0.177 · 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

Citations26
Published2011
Admission routes2
Has abstractyes

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