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Record W3139074588 · doi:10.3390/chemosensors9030058

Advances in Electromagnetic Piezoelectric Acoustic Sensor Technology for Biosensor-Based Detection

2021· article· en· W3139074588 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemosensors · 2021
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Resonator Technologies
Canadian institutionsUniversity of Toronto
FundersNemzeti Kutatási Fejlesztési és Innovációs HivatalNatural Sciences and Engineering Research Council of CanadaYasouj UniversityEuropean Commission
KeywordsBiosensorPiezoelectricityMaterials scienceAcousticsElectromagnetic coilHarmonicsOscillation (cell signaling)Sensitivity (control systems)OptoelectronicsElectrical engineeringVoltageElectronic engineeringNanotechnologyEngineeringPhysicsChemistry

Abstract

fetched live from OpenAlex

The ultra-high frequency EMPAS (electromagnetic piezoelectric acoustic sensor) device is composed of an electrode-less quartz disc in which shear oscillation is induced by an AC-powered magnetic coil located 30 μm below the substrate. This configuration allows the instigation of high acoustic harmonics (in the region of 49th–53rd), with the resulting enhanced analytical sensitivity for biosensor purposes compared to the conventional thickness-shear mode device. In this paper, we introduce significant improvements to the operation of the system with respect to sensing applications. This includes a new interface program and the capability to measure the acoustic quality factor not available in the prototype version. The enhanced configuration is subject to testing through biosensor detection of surface adsorption of biological macromolecules, which include β-casein, and a gelsolin-actin complex.

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.

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)0.001
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: Empirical
Teacher disagreement score0.176
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.005
GPT teacher head0.214
Teacher spread0.208 · 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