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Record W2186907208

YARN BASED MICROFLUIDICS: FROM BASIC ELEMENTS TO COMPLEX CIRCUITS

2009· article· en· W2186907208 on OpenAlexaff
Roozbeh Safavieh, Maryam Mirzaei, Mohammad A. Qasaimeh, David Juncker

Bibliographic record

Venue13th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2009 · 2009
Typearticle
Languageen
FieldEngineering
TopicBiosensors and Analytical Detection
Canadian institutionsMcGill University
Fundersnot available
KeywordsMicrofluidicsYarnElectronic circuitNanotechnologyComputer scienceTopology (electrical circuits)Materials scienceEngineeringMechanical engineeringElectrical engineering
DOInot available

Abstract

fetched live from OpenAlex

Microfluidics are being used in diagnostics, but their relative high cost has prevented their adoption in low resource settings so far. Here we present yarn based microfluidics with the potential for low cost manufacture. We describe methods to control the hydrophilicity of the yarn, its encapsulation, and how to make self-powered microfluidic circuits based on capillary force. Branched microfluidics were made by knotting two or more threads to one another. We discovered that knots are effective mixers, and that a different topology leads to different mixing results. We demonstrate a complex circuit using a mesh with hydrophilic, hydrophobic and selectively coated yarns and use it for transporting and routing different fluids along separate paths.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.532
Threshold uncertainty score0.907

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 head0.044
GPT teacher head0.277
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 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

Citations4
Published2009
Admission routes1
Has abstractyes

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