MétaCan
Menu
Back to cohort
Record W2104580763 · doi:10.1039/b209030a

An acoustic wave sensor incorporated with a microfluidic chip for analyzing muscle cell contraction

2003· article· en· W2104580763 on OpenAlexaff
Paul C. H. Li, Weijie Wang, M. Parameswaran

Bibliographic record

VenueThe Analyst · 2003
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Resonator Technologies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMicrofluidicsMicrofluidic chipMaterials scienceElectrodeViscoelasticityChipBiomedical engineeringStiffnessContraction (grammar)Lab-on-a-chipDetectorFabricationNanotechnologyOptoelectronicsChemistryComposite materialOpticsElectrical engineering

Abstract

fetched live from OpenAlex

We report the fabrication of a microfluidic chip or lab-on-a-chip integrated with a thickness-shear mode (TSM) acoustic wave sensor for muscle cell analysis. The sensor, essentially an AT-cut quartz crystal, serves as a detector for recording changes in acoustic wave properties occurring in an attached cardiomyocyte (single heart muscle cell) during its contraction and relaxation. Presumably, the changes resulted from alterations in viscoelastic properties (e.g. stiffness) of the cells. The effects of excitation electrode size, the presence of a microfluidic channel plate, and liquid loading on the sensor were first examined. Thereafter, muscle cell contraction analysis upon chemical stimuli were described. The potential of the chip for screening of cardiovascular drugs is discussed.

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)0.001
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: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.013
GPT teacher head0.210
Teacher spread0.197 · 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

Citations47
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueThe AnalystSame topicAcoustic Wave Resonator TechnologiesFrench-language works237,207