MétaCan
Menu
Back to cohort

Neural Control of Muscle

2014· book-chapter· en· W2500264525 on OpenAlexaff
Parveen Bawa, Kelvin E. Jones

Bibliographic record

VenueAdvances in medical technologies and clinical practice book series · 2014
Typebook-chapter
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsUniversity of AlbertaSimon Fraser University
Fundersnot available
KeywordsMotor unitNeuroscienceMotor controlPopulationComputer scienceCognitive sciencePsychologyMedicine

Abstract

fetched live from OpenAlex

The purpose of this chapter is to introduce the reader to the development of ideas and concepts about the manner in which the central nervous system controls muscle contraction. The motor unit, the quantum of muscle contraction, is fundamental to concepts of the neural control of muscle and will be the focus of discussion. The population of motor units comprising a skeletal muscle have a diverse range of physiological and anatomical properties. The Size Principle of motor unit recruitment is a concept that proposes a simple strategy for exploiting the diversity of the motor unit population to produce graded force output. The Size Principle has a great deal of empirical support, but also faces criticism about the extent of generalization to all types and forms of movement. As the key principles of motor units are discussed, methods of measuring and methodology for analysing motor unit activity and whole muscle activities are introduced.

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)0.000
metaresearch head score (Gemma)0.000
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: Other · Consensus signal: Other
Teacher disagreement score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.007

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 head0.012
GPT teacher head0.301
Teacher spread0.289 · 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
GenreOther

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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueAdvances in medical technologies and clinical practice book seriesSame topicMuscle activation and electromyography studiesFrench-language works237,207