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Record W2030385259 · doi:10.1088/1748-6041/2/1/s02

Electrode–tissues interface: modeling and experimental validation

2007· review· en· W2030385259 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBiomedical Materials · 2007
Typereview
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsMcGill UniversityPolytechnique Montréal
FundersCanadian Institutes of Health ResearchHealth CanadaCanada Research Chairs
KeywordsElectrical impedanceMaterials scienceReliability (semiconductor)VoltageInterface (matter)ElectrodeController (irrigation)Generator (circuit theory)Computer scienceElectronic engineeringElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

The electrode-tissues interface (ETI) is one of the key issues in implantable devices such as stimulators and sensors. Once the stimulator is implanted, safety and reliability become more and more critical. In this case, modeling and monitoring of the ETI are required. We propose an empirical model for the ETI and a dedicated integrated circuit to measure its corresponding complex impedance. These measurements in the frequency range of 1 Hz to 100 kHz were achieved in acute dog experiments. The model demonstrates a closer fitting with experimental measurements. In addition, a custom monitoring device based on a stimuli current generator has been completed to evaluate the phase shift and voltage across the electrodes and to transmit wirelessly the values to an external controller. This integrated circuit has been fabricated in a CMOS 0.18 microm process, which consumes 4 mW only during measurements and occupies an area of 1 mm(2).

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.325
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.126
GPT teacher head0.408
Teacher spread0.282 · 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