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Record W2331532816 · doi:10.1115/imece2005-80223

Electrokinetic Focusing and Dispensing of Particles and Cells on Microfluidic Chips

2005· article· en· W2331532816 on OpenAlexaff
Xiangchun Xuan, Edmond W. K. Young, Dongqing Li

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsElectrokinetic phenomenaMicrofluidicsMaterials scienceElectrophoresisNanotechnologyLab-on-a-chipPolystyreneBlood streamChemistryChromatographyPolymerComposite material

Abstract

fetched live from OpenAlex

This work investigated the electrokinetic focusing and dispensing of polystyrene particles and red blood cells on microfluidic chips. Particles or cells were first electrokinetically focused using the merging of focusing streams on the sample stream, and subsequently separated as a result of the focusing. These particles or cells were then selectively dispensed from the focused sample stream using precise application of electrical pulses. The whole process of focusing, separation and dispensing of particles was visualized by a custom-made microscopy system. In particular, the width of the focused fluorescein stream and the accelerated electrophoretic motion of particles and cells were measured in a cross-channel and compared with a proposed analytical model. The electrokinetic manipulation of particles and cells demonstrated in this work can be used for developing integrated lab-on-a-chip devices for studies of cells.

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.006
GPT teacher head0.175
Teacher spread0.169 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

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