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Record W2532608858 · doi:10.1109/iembs.1991.684218

Evaluation Of Simulated Motor Unit Action Potentials

2005· article· en· W2532608858 on OpenAlexaff
Daniel W. Stashuk, R.K. Naphan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMotor unitConcentricElectromyographyComputer sciencePopulationPattern recognition (psychology)Biomedical engineeringArtificial intelligenceMathematicsAnatomyEngineeringPhysical medicine and rehabilitationMedicineGeometry

Abstract

fetched live from OpenAlex

METHODS Several characteristic features of individual motor unit action potentials (MUAPs) were extracted from populations of simulated MUAPs and compared to similar features extracted from populations of real MUAPs. MUAPs simulated as if detected by both concentric and monopolar needle electrodes were studied. The comparison was an attempt to evaluate the underlying model used for the simulation of the MUAPs and to verify specific values used for many of the parameters of the model. The comparative values for features extracted from real MUAPs were obtained from the literature [1,2]. Overall, the population of simulated MUAPs tended to be too complex and to have durations which were too short. Nonetheless, the results in a quantitative way validate the simulation model and suggest adjustment to several of the model parameter values.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.055
GPT teacher head0.298
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations2
Published2005
Admission routes1
Has abstractyes

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