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Record W2460786307 · doi:10.1385/1-59259-798-x:001

Surfactant-Based Methods for Prevention of Protein Adsorption in Capillary Electrophoresis

2004· article· en· W2460786307 on OpenAlexafffund
Charles A. Lucy, Nicole E. Baryla, Ken K.‐C. Yeung

Bibliographic record

VenueHumana Press eBooks · 2004
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsWestern UniversityAlberta Glycomics CentreEli Lilly (Canada)University of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of AlbertaEli Lilly and Company
KeywordsCationic polymerizationPulmonary surfactantBilayerCapillary electrophoresisChemistryAdsorptionChemical engineeringElectrophoresisCoatingPhosphatidylcholineAmmonium bromideBromideChromatographyLipid bilayerPolymer chemistryOrganic chemistryMembranePhospholipidBiochemistry

Abstract

fetched live from OpenAlex

Surfactants such as didodecyldimethyl ammonium bromide (DDAB) and 1,2-dilauroyl-sn-phosphatidylcholine (DLPC) form bilayers at the walls of bare silica capillaries. Once formed, these bilayers are stable in the absence of surfactant in the buffer. DDAB provides a cationic bilayer coating which yields a strong reversed EOF and is effective for separation of cationic proteins. DLPC provides a zwitterionic bilayer coating which is effective for both cationic and anionic proteins. The electroosmotic flow (EOF) is strongly suppressed in DLPC-coated capillaries, thus low mobility proteins are slow to elute, and so the coating is favored for separation of high mobility proteins.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.029
GPT teacher head0.292
Teacher spread0.263 · 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

Citations5
Published2004
Admission routes2
Has abstractyes

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