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Record W1998036599 · doi:10.1109/tbme.2013.2241061

Development of Surrogate Spinal Cords for the Evaluation of Electrode Arrays Used in Intraspinal Implants

2013· article· en· W1998036599 on OpenAlexaff
Cheng Cheng, Jonn Kmech, Vivian K. Mushahwar, Anastasia Elias

Bibliographic record

VenueIEEE Transactions on Biomedical Engineering · 2013
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsUniversity of Alberta
FundersNational Institute of Neurological Disorders and Stroke
KeywordsMaterials scienceGelatinSpinal cordBiomedical engineeringElectrodeModulusComposite materialChemistryMedicine

Abstract

fetched live from OpenAlex

We report the development of a surrogate spinal cord for evaluating the mechanical suitability of electrode arrays for intraspinal implants. The mechanical and interfacial properties of candidate materials (including silicone elastomers and gelatin hydrogels) for the surrogate cord were tested. The elastic modulus was characterized using dynamic mechanical analysis, and compared with values of actual human spinal cords from the literature. Forces required to indent the surrogate cords to specified depths were measured to obtain values under static conditions. Importantly, to quantify surface properties in addition to mechanical properties normally considered, interfacial frictional forces were measured by pulling a needle out of each cord at a controlled rate. The measured forces were then compared to those obtained from rat spinal cords. Formaldehyde-crosslinked gelatin, 12 wt% in water, was identified as the most suitable material for the construction of surrogate spinal cords. To demonstrate the utility of surrogate spinal cords in evaluating the behavior of various electrode arrays, cords were implanted with two types of intraspinal electrode arrays (one made of individual microwires and another of microwires anchored with a solid base), and cord deformation under elongation was evaluated. The results demonstrate that the surrogate model simulates the mechanical and interfacial properties of the spinal cord, and enables in vitro screening of intraspinal implants.

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 score0.403
Threshold uncertainty score0.395

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.069
GPT teacher head0.310
Teacher spread0.241 · 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

Citations11
Published2013
Admission routes1
Has abstractyes

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