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Record W2536639902 · doi:10.1109/embc.2016.7592034

A wide range and high sensitivity four-channel compact electrochemical biosensor for neurotransmitter detection on a microfluidic platform

2016· article· en· W2536639902 on OpenAlexafffund
Elnaz Ghodsevali, Hamza Landari, Mounir Boukadoum, Benoit Gosselin, Amine Miled

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsUniversité du Québec à MontréalUniversité Laval
FundersNational Research Council Canada
KeywordsPotentiostatBiosensorMicrofluidicsMaterials scienceSensitivity (control systems)OptoelectronicsElectrodeAnalytical Chemistry (journal)NanotechnologyElectronic engineeringChemistryElectrochemistryChromatographyEngineering

Abstract

fetched live from OpenAlex

We present a four-channel, high-sensitivity and linearity electrochemical biosensor for neurotransmitter (NT) detection and measurement. Using a multi-channel microfluidic platform makes this biosensor capable of detecting NT-related currents going from nanoamperes to milliamperes, with a sensitivity of the order of picoamperes. Moreover, by using a fully differential potentiostat architecture, the biosensor offers a high common-mode rejection ratio (90 dB), making it appropriate for low-noise and high-sensitive applications. The system was implemented on a 15 mm × 15 mm PCB with direct interface to the microfluidic chambers. It was calibrated with a 5 mM ferrocyanide solution and successfully tested with dopamine at three concentrations. The system shows a minimum sensistivity of 100 pA and consumes 60 mW.

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 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: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.547

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)0.0000.000

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 head0.037
GPT teacher head0.238
Teacher spread0.200 · 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.

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

Citations2
Published2016
Admission routes2
Has abstractyes

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