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Record W2119037156 · doi:10.1109/iscas.2011.5938074

A new fully integrated CMOS interface for a dielectrophoretic lab-on-a-chip device

2011· article· en· W2119037156 on OpenAlexafffund
Mohamed Amine Miled, Mohamad Sawan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCMC Microsystems
KeywordsCMOSCapacitive sensingDielectrophoresisChipSIGNAL (programming language)MicrochannelResistive touchscreenVoltageElectrical engineeringMaterials scienceElectronic engineeringMicrofluidicsOptoelectronicsEngineeringComputer scienceNanotechnology

Abstract

fetched live from OpenAlex

We present in this paper a new CMOS interface for cell manipulation by dielectrophoresis and capacitive sensing system dedicated for a lab-on-a-chip. It fully integrates a signal generation circuit and a post-processing system to control parameters of each signal such as frequency, phase and amplitude. In addition, a large capacitive and low resistive load driver circuit is designed to deliver a current of 9 mA for each 16 electrodes as the microfluidic architecture is divided into 4 blocs containing 16 electrodes each one. Thus, the proposed CMOS chip provides 4-channel signals with individually controllable phase and amplitude. In addition, a capacitive sensing system has been integrated into the same chip to detect the capacitive change in the microchannel in the Lab-on-a-chip. The generated signals have a 2.5 peak-to-peak voltage range and 70 kHz frequency range while the detection system has a dynamic range of 1.5 V and a sensitivity of 11.8 fF/V.

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: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.025
GPT teacher head0.218
Teacher spread0.192 · 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

Citations3
Published2011
Admission routes2
Has abstractyes

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