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Record W2060323122 · doi:10.1109/tcsi.2013.2248771

Chopper-Stabilized Bidirectional Current Acquisition Circuits for Electrochemical Amperometric Biosensors

2013· article· en· W2060323122 on OpenAlexaff
Hamed Mazhab Jafari, Roman Genov

Bibliographic record

VenueIEEE Transactions on Circuits and Systems I Regular Papers · 2013
Typearticle
Languageen
FieldChemical Engineering
TopicAnalytical Chemistry and Sensors
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTransimpedance amplifierChopperCascodeElectronic circuitFlicker noiseInterfacingMaterials scienceBiosensorCurrent (fluid)CMOSCurrent mirrorElectrical engineeringElectronic engineeringAmperometryAmplifierOptoelectronicsComputer scienceOperational amplifierTransistorNanotechnologyVoltageElectrodeEngineeringElectrochemistryChemistryComputer hardwareNoise figure

Abstract

fetched live from OpenAlex

Two low-noise bidirectional current acquisition circuits for interfacing with electrochemical amperometric biosensor arrays are presented. The first design is a switched-capacitor transimpedance amplifier (TIA). The second design is a current conveyer (CC) with regulated-cascode current mirrors. Both circuits employ chopper stabilization to reduce flicker noise. The TIA and the CC were prototyped in 0.13 μm CMOS and consume 3 μW and 4 μW from a 1.2 V supply, respectively. The electrical and electrochemical recording properties of both circuits have been characterized. The current conveyer exhibits superior performance in low-concentration electrochemical catalytic reporter sensing, as less switching noise is injected into the biosensor.

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)0.002
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.018
GPT teacher head0.233
Teacher spread0.215 · 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

Citations68
Published2013
Admission routes1
Has abstractyes

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Same venueIEEE Transactions on Circuits and Systems I Regular PapersSame topicAnalytical Chemistry and SensorsFrench-language works237,207