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Record W4220960265 · doi:10.3390/bios12040194

A V-Shaped Microcantilever Sensor Based on a Gap Method for Real-Time Detection of E. coli Bacteria

2022· article· en· W4220960265 on OpenAlexafffund
Jino Fathy, Yongjun Lai

Bibliographic record

VenueBiosensors · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMechanical and Optical Resonators
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBacteriaMicrobiologyEscherichia coliMaterials scienceChemistryChromatographyBiologyBiochemistry

Abstract

fetched live from OpenAlex

This paper presents a dynamic-mode microcantilever sensor based on a gap method. The sensor has a V-shaped microcantilever and a fixed structure at a distance of 2 µm from its free end. The microcantilever is excited by applying an ac electric potential (3 Vp) to its piezoelectric pads and vibrates at its fundamental resonant frequency. An independent ac electric potential (200 kHz, 15 Vpp) is applied to the fixed structure. This creates a non-uniform electric field with its maxima at the gap and exerts a dielectrophoresis (DEP) force. The DEP force attracts and adsorbs the E. coli bacteria to the cantilever edge at the gap. The binding of the bacteria to the cantilever creates a shift in the resonant frequency of the microcantilever sensor, which is detected by a laser vibrometer. The real-time detection of E. coli bacteria samples, diluted in distilled water, was performed for concentrations of 105–103 cells/mL and the real-time frequency shifts were −2264.3 to −755 Hz in 4 min, respectively. The tests were expanded to study the effect of the electric potential amplitude (10, 12, 15 Vpp) and higher frequency shifts were observed for higher amplitudes.

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 categoriesInsufficient payload (model declined to judge)
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 score0.309
Threshold uncertainty score0.999

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)0.0020.000

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 head0.017
GPT teacher head0.267
Teacher spread0.250 · 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.

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

Citations6
Published2022
Admission routes2
Has abstractyes

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