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Record W4415671848 · doi:10.1109/jmems.2025.3621147

Microcapillary Electrophoresis Device Fabrication Using Ultraviolet Laser Ablation: Application for Detection of Levofloxacin in Dairy

2025· article· W4415671848 on OpenAlexafffund
Sean S. Worthington, Seth N. Lowry, M Richardson, Christopher M. Collier

Bibliographic record

VenueJournal of Microelectromechanical Systems · 2025
Typearticle
Language
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsMicrochannelFabricationCapillary electrophoresisMicrofluidicsUltravioletLaserElectrophoresis

Abstract

fetched live from OpenAlex

This work explores a fabrication technique for producing glass-based microfluidic devices for the purpose of performing capillary electrophoresis analysis of biochemical samples, including the detection of fluoroquinolone-class antibiotics in cow’s milk. This exploration employs ultraviolet laser ablation to produce high-quality microcapillaries in two low-cost glass substrates: soda-lime glass and borosilicate glass. This technique enables the in-house fabrication of such devices without the need for caustic chemical etchants and yields smooth channel surfaces capable of inducing electroosmotic flow. This study provides a thorough characterization of the laser milling system, demonstrating the relationship between optical fluence and microchannel cut depth and quality. Furthermore, a practical application of the microfluidic device is demonstrated experimentally via an electrophoretic separation of a cow’s milk sample containing the antibiotic levofloxacin. This experiment showed a detection time of less than 5 minutes. [2025-0131]

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)0.000
metaresearch head score (Gemma)0.000
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.010
GPT teacher head0.242
Teacher spread0.233 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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