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Record W1689693979 · doi:10.1109/mwscas.1994.519206

Design optimization of a current source for microstimulator applications

2002· article· en· W1689693979 on OpenAlexaffabout
Robert St-Amand, Yvon Savaria, Mohamad Sawan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsMicroelectronicsCurrent sourceCurrent (fluid)CMOSElectrical engineeringElectronic engineeringComputer scienceCapacitorCircuit designIntegrated circuit designEngineeringVoltage

Abstract

fetched live from OpenAlex

The main goal of our study is the design of a current source (CS) based on a miniaturized digital-to-analog converter (DAC). The primary application of this device is a wide range of neuromuscular implantable microstimulators. Special attention is paid to design a flexible, compact and energy efficient circuit. A new design method is thus proposed. This method was applied to the design of a 5-bit, 3 mA peak current source, whose active circuit area is only 0.01 mm/sup 2/. This current source has been submitted for implementation in the 1.2 /spl mu/m CMOS technology offered by the Canadian Microelectronics Corporation.

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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score0.229

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 head0.112
GPT teacher head0.297
Teacher spread0.185 · 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
GenreMethods

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

Citations6
Published2002
Admission routes2
Has abstractyes

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