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Record W2034663400 · doi:10.1109/mecbme.2014.6783223

Low power CMOS neurochemical biosensor application in an implantable intelligent neurotrophic factor delivery hybrid microsystem for Parkinson's

2014· article· en· W2034663400 on OpenAlexaff
Mohammad Poustinchi, Sam Musallam

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsMcGill University
Fundersnot available
KeywordsMicrosystemCMOSBiosensorNeurochemicalElectronic engineeringComparatorNeurotrophic factorsElectronic circuitNeuromodulationComputer scienceMaterials scienceElectrical engineeringEngineeringNanotechnologyNeuroscienceVoltageChemistryCentral nervous system

Abstract

fetched live from OpenAlex

We have developed a low power neurotransmitter biosensor which can be applied in an implantable closed-loop CMOS neurotrophic factor delivery microsystem which by protecting the healthy neurons and restoring damaged ones can maintain therapeutic levels of chemical concentrations in the brain. The hybrid microsystem is composed of novel biosensor that can sense micromolar concentration of neurotransmitters (dopamine) and embedded negative feedback circuits that control the flow of pharmacological agents in micro fluidic channels. The focus of this manuscript is on sensing, control and decision making circuitry. It consists of a current conveyer, a low noise low power amplifier, an integrator and a comparator with offset cancelation. Circuit is fabricated in CMOS 0.18 um with low power consumption of 921 nW.

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 score0.053
Threshold uncertainty score0.954

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 science0.0010.000
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 head0.022
GPT teacher head0.252
Teacher spread0.230 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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