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Record W4386466679 · doi:10.1152/jn.00132.2023

Voluntary activation does not differ when using two different methods to determine transcranial magnetic stimulator output

2023· article· en· W4386466679 on OpenAlexafffund
Christina D. Bruce, Justine R. Magnuson, Chris J. McNeil

Bibliographic record

VenueJournal of Neurophysiology · 2023
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersCanada Foundation for InnovationNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsTranscranial magnetic stimulationElectromyographyPhysical medicine and rehabilitationStimulationLimitingMedicinePsychologyCardiologyInternal medicine

Abstract

fetched live from OpenAlex

When using transcranial magnetic stimulation (TMS) to determine voluntary activation (VA) of the elbow flexors, we hypothesized that a stimulator output designed to limit antagonist muscle activity would evoke submaximal agonist superimposed twitch amplitudes, thus underestimating VA. Contrary to our hypothesis, VA was not greater with an output based on maximal superimposed twitch amplitude. Nevertheless, our findings advance methodological practices by simplifying the equipment and minimizing the time required to determine VA using TMS.

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)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.295
Teacher spread0.259 · 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 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

Citations1
Published2023
Admission routes2
Has abstractyes

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