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Record W2903368432 · doi:10.1002/mus.26391

A modified multiple point stimulation method for motor unit number estimation of the hypothenar muscles

2018· article· en· W2903368432 on OpenAlexaff
Akiko Hachisuka, K. Ming Chan

Bibliographic record

VenueMuscle & Nerve · 2018
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsUniversity of Alberta
FundersJapan Society for the Promotion of Science
KeywordsMotor unitStimulationMedicineEstimationPhysical medicine and rehabilitationMathematicsAnatomyInternal medicineEngineering

Abstract

fetched live from OpenAlex

INTRODUCTION: The goal of this study is to test the hypothesis that single motor unit action potentials (SMUPs) originating from other ulnar nerve-innervated intrinsic hand muscles can inflate the motor unit number estimation (MUNE) of the hypothenar muscles. METHODS: Using the multiple point stimulation method, SMUPs recorded over the hypothenar muscles from distant origins were characterized through multichannel recordings. The MUNE calculated using only the hypothenar SMUPs was compared with estimations based on the whole ensemble. RESULTS: Of the 41 studies performed, distant SMUPs represented 17 ± 9.5% (mean ± SD) of the overall sample. MUNE calculated using only hypothenar SMUPs was 423 ± 204, compared with 537 ± 290 if all SMUPs were included (P < 0.05). The extent of increase in MUNE was highly correlated with the proportion of distant SMUPs found (r = 0.89, P < 0.05). DISCUSSION: Erroneous inclusion of SMUPs from distant muscles can significantly distort the MUNE results. Muscle Nerve 59:337-341, 2019.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.588
Threshold uncertainty score0.473

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 head0.028
GPT teacher head0.271
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 teacher head, 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

Citations5
Published2018
Admission routes1
Has abstractyes

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