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Record W2083208715 · doi:10.1109/memsys.2013.6474225

Magnetic valves with programmable timing capability for fluid control in paper-based microfluidics

2013· article· en· W2083208715 on OpenAlexaff
Philip Zwanenburg, X. Li, X. Y. Liu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicBiosensors and Analytical Detection
Canadian institutionsMcGill University
Fundersnot available
KeywordsMicrofluidicsResistorFluidicsComputer scienceFlow control (data)Materials scienceVoltageElectrical engineeringNanotechnologyEngineering

Abstract

fetched live from OpenAlex

Multi-step analytical tests such as enzyme-linked immunosorbent assay (ELISA) require delivery of multiple fluids into a reaction zone and counting of incubation time at different steps. This paper presents a new type of paper-based magnetic valves that can count the time and turn on or off a fluidic flow accordingly, enabling timed fluid control in paper-based microfluidics. The timing function of these valves is realized using a paper timing channel with an ionic resistor, which can detect the event of a solution flowing through the resistor and trigger an electromagnet (through a simple circuit) to open or close a paper cantilever valve. Based on this principle, we developed normally-open and normally-closed valves with a timing period up to 30.3±2.1 minutes (sufficient for ELISA on paper-based platforms). Using the normally-open valve, we performed an enzyme-based colorimetric reaction commonly used for signal amplification of ELISAs, which requires a timed delivery of enzyme substrate to a reaction zone. This design adds a new fluid-control component to the tool set for developing paper-based microfluidic devices, and has the potential to improve the user-friendliness of these devices.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.918
Threshold uncertainty score0.331

Codex and Gemma teacher scores by category

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 integrity0.0000.000
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 head0.007
GPT teacher head0.186
Teacher spread0.179 · 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.

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

Citations5
Published2013
Admission routes1
Has abstractyes

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