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Implantable Electronics for the Recovery of Neuromuscular Functions

2008· article· en· W1968765794 on OpenAlex
Mohamad Sawan, Benoit Gosselin, Jonathan Coulombe, Amer Elias Ayoub, Ananish Chaudhuri, Frank Louis Lepore

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAdvances in science and technology · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsUniversité de MontréalMcGill UniversityPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCMC Microsystems
KeywordsMicrosystemMicrostimulationReliability (semiconductor)NeuroprostheticsElectronicsMaterials scienceWirelessComputer scienceElectronic engineeringElectrical engineeringPower (physics)NanotechnologyEngineeringStimulationNeuroscience

Abstract

fetched live from OpenAlex

This paper covers circuits and systems techniques for the construction of high reliability biosensing and stimulation medical devices. Such microsystems are dedicated for interconnections through either the central or the peripheral nervous systems. Low-power high-reliability wireless links are used to power up the implanted devices while data are exchanged bidirectionaly between these implants and external controllers. A global view of main devices is given, case studies related to applications such as bladder control, intracortical monitoring and microstimulation are discussed, altogether with modeling, characterization, as well as microsystems assembly and packaging. Also, dedicated electrode arrays and their interfaces to tissues interfaces are summarized.

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)0.001
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 score0.046
Threshold uncertainty score0.559

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.002
Scholarly communication0.0000.001
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 head0.016
GPT teacher head0.263
Teacher spread0.247 · 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