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Record W2322200776 · doi:10.1021/ac1024478

Non-contact Addition, Metering, and Distribution of Liquids into Centrifugal Microfluidic Devices in Motion

2010· article· en· W2322200776 on OpenAlexafffund
Adam P. Bouchard, David A. Duford, Eric D. Salin

Bibliographic record

VenueAnalytical Chemistry · 2010
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Council
KeywordsMicrofluidicsChemistryCentrifugal forceMetering modeVolume (thermodynamics)Microfluidic chipMacroRelative standard deviationNanotechnologyMechanicsChromatographyMechanical engineeringThermodynamicsEngineeringComputer science

Abstract

fetched live from OpenAlex

A three-dimensional structure was constructed to demonstrate contact-free liquid addition and distribution to a conventional centrifugal microfluidic platform. The structure allowed a continuous stream of liquid to be added to the rotating platform where it was dispensed and metered to a series of reservoirs with 9% relative standard deviation of the volume. An off-platform generated gradient was used to demonstrate this design's potential to make gradient centrifugal microfluidic chromatography possible without the use of platform space for liquid storage. The system demonstrates a convenient and versatile "World-to-Chip" or more appropriately, World-to-Disk, macro-to-micro interface.

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)0.001
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.003
GPT teacher head0.202
Teacher spread0.199 · 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

Citations14
Published2010
Admission routes2
Has abstractyes

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