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Record W2069442582 · doi:10.1002/elps.200900334

Capillary electrochromatography with packed bead beds in microfluidic devices

2009· article· en· W2069442582 on OpenAlexaff
Abebaw B. Jemere, Dolores Barranco Martínez, Michael Finot, D. Jed Harrison

Bibliographic record

VenueElectrophoresis · 2009
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsUniversity of AlbertaNational Research Council CanadaNational Institute for Nanotechnology
Fundersnot available
KeywordsCapillary electrochromatographyElectrochromatographyChromatographyAnalyteBeadChemistryMicrofluidicsSize-exclusion chromatographyAnalytical Chemistry (journal)Materials scienceCapillary electrophoresisNanotechnology

Abstract

fetched live from OpenAlex

Microchip-based bead-packed columns for electrochromatography are described for several types of stationary phases. Chromatography columns 2 mm in length were used for the separation of proteins and peptides by size- and ion-exchange modes of separation, respectively. In size-exclusion electrochromatograpgy, FITC-IgG and FITC-insulin were baseline resolved in less than 10 s, with efficiencies of up to 139,000 plates/m for FITC-insulin. In strong cation-exchange electrochromatography, a mixture of three fluorescently labeled peptides was baseline resolved in less than 40 s, with efficiencies up to 400,000 plates/m. The RSD for the analytes retention times were<3% in both size-exclusion and ion-exchange modes of separations. The use of a 1-mm-long reverse-phase column for the semiquantitative evaluation of pharmaceutical formulations in drug solubility tests illustrates the use of this microfluidic chip-based electrochromatographic approach to drug development.

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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.003
GPT teacher head0.181
Teacher spread0.178 · 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

Citations20
Published2009
Admission routes1
Has abstractyes

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