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Record W3168687488 · doi:10.1249/jes.0000000000000264

Enhancing Adaptations to Neuromuscular Electrical Stimulation Training Interventions

2021· review· en· W3168687488 on OpenAlexaff
Anthony J. Blazevich, David F. Collins, Guillaume Y. Millet, Marco Aurélio Vaz, Nicola A. Maffiuletti

Bibliographic record

VenueExercise and Sport Sciences Reviews · 2021
Typereview
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPhysical medicine and rehabilitationStimulationRehabilitationStimulus (psychology)Muscle fatigueMedicineFunctional electrical stimulationPsychological interventionPhysical therapyElectromyographyPsychologyInternal medicine

Abstract

fetched live from OpenAlex

Neuromuscular electrical stimulation (NMES) applied to skeletal muscles is an effective rehabilitation and exercise training modality. However, the relatively low muscle force and rapid muscle fatigue induced by NMES limit the stimulus provided to the neuromuscular system and subsequent adaptations. We hypothesize that adaptations to NMES will be enhanced by the use of specific stimulation protocols and adjuvant interventions.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.115
GPT teacher head0.356
Teacher spread0.240 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations70
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueExercise and Sport Sciences ReviewsSame topicMuscle activation and electromyography studiesFrench-language works237,207