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Record W2133849398 · doi:10.1109/tcsi.2006.884425

16-Channel Integrated Potentiostat for Distributed Neurochemical Sensing

2006· article· en· W2133849398 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.

Bibliographic record

VenueIEEE Transactions on Circuits and Systems I Fundamental Theory and Applications · 2006
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPotentiostatChronoamperometryVery-large-scale integrationElectronic engineeringDynamic rangeBandwidth (computing)BiCMOSMaterials scienceElectrical engineeringCyclic voltammetryComputer scienceChemistryElectrodeEngineeringVoltageElectrochemistryTelecommunications

Abstract

fetched live from OpenAlex

We present the architecture and VLSI circuit implementation of a BiCMOS potentiostat bank for monitoring neurotransmitter concentration on a screen-printed carbon electrode array. The potentiostat performs simultaneous acquisition of bidirectional reduction-oxidation currents proportional to neurotransmitter concentration on 16 independent channels at controlled redox potentials. Programmable current gain control yields over 100-dB cross-scale dynamic range with 46-pA input-referred rms noise over 12-kHz bandwidth. The cutoff frequency of a second-order log-domain anti-aliasing filter ranges from 50 Hz to 400 kHz. Track-and-hold current integration is triggered at the sampling rate between dc and 200 kHz. A 2.25-mmtimes2.25-mm prototype was fabricated in a 1.2-mum VLSI technology and dissipates 12.5 mW. Chronoamperometry dopamine concentration measurements results are given. Other types of neurotransmitters can be selected by adjusting the redox potential on the electrodes and the surface properties of the sensor coating

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.805
Threshold uncertainty score0.626

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 studies0.0010.000
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 head0.024
GPT teacher head0.247
Teacher spread0.223 · 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