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Record W3080566271 · doi:10.1002/elps.202000116

Voltage control for microchip capillary electrophoresis analyses

2020· article· en· W3080566271 on OpenAlexafffund
Rick Bosma, Jasen Devasagayam, Rahul Eswar, Iasmin de França Albuquerque, Christopher M. Collier

Bibliographic record

VenueElectrophoresis · 2020
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationOntario Centres of Excellence
KeywordsVoltageCapillary electrophoresisInterface (matter)MicrocontrollerInstrumentation (computer programming)Computer scienceSIGNAL (programming language)Sample (material)Computer hardwareController (irrigation)FluidicsElectrical engineeringMaterials scienceCapillary actionEngineeringChromatographyChemistry

Abstract

fetched live from OpenAlex

This paper presents an inexpensive and easy-to-implement voltage sequencer instrument for use in microchip capillary electrophoresis (MCE) actuation. The voltage sequencer instrument takes a 0-5 V input signal from a microcontroller and produces a reciprocally proportional voltage signal with the capability to achieve the voltages required for MCE actuation. The unit developed in this work features four independent voltage channels, measures 105 × 143 × 45 mm (width × length × height), and the cost to assemble is under 60 USD. The system is controlled by a peripheral interface controller and commands are given via universal serial bus connection to a personal computer running a command line graphical user interface. The performance of the voltage sequencer is demonstrated by its integration with a fluorescence spectroscopy MCE sensor using pinched sample injection and electrophoretic separation to detect ciprofloxacin in samples of milk. This application is chosen as it is particularly important for the dairy industry, where fines and health concerns are associated with the shipping of antibiotic-contaminated milk. The voltage sequencer instrument presented represents an effective low-cost instrumentation method for conducting MCE, thereby making these experiments accessible and affordable for use in industries such as the dairy industry.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.635
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.243
Teacher spread0.224 · 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 teacher head, not a consensus.

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

Citations12
Published2020
Admission routes2
Has abstractyes

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