MétaCan
Menu
Back to cohort
Record W68414940 · doi:10.55782/ane-2014-1982

Cutaneous afferent regulation of motor function

2014· review· en· W68414940 on OpenAlexafffund
Izabela Panek, Tuan V. Bui, Asher Wright, Robert M. Brownstone

Bibliographic record

VenueActa Neurobiologiae Experimentalis · 2014
Typereview
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsUniversity of OttawaDalhousie University
FundersCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsNeuroscienceSensory systemGRASPMotor systemMotor functionAfferentMotor controlPsychologyPhysical medicine and rehabilitationBiologyMedicineComputer science

Abstract

fetched live from OpenAlex

Motor systems must be responsive to the environment in which the organism moves. Accordingly, there are many sensory systems that affect intrinsic motor programs. In this mini review, we will discuss the effects that inputs from cutaneous low-threshold mechanoreceptors have on motor function, focusing on locomotion and hand grasp. A mathematical analysis of grip strength is provided to quantify the regulation of the forces required in maintaining the grip of a moving object. These two behaviours were selected because the neural control of locomotion has been primarily studied for hind-limbs in cats and rodents, whereas hand grasp has been primarily studied in fore-limbs in human and non-human primates. When taken together, insight can be gleaned on the cutaneous regulation of movement as well as the role these afferents may play in mediating functional recovery following injury. We conclude that low-threshold mechanoreceptors are critical for normal motor function and for inducing plasticity in motor microcircuits following injury.

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: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.024
GPT teacher head0.263
Teacher spread0.239 · 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

Citations30
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueActa Neurobiologiae ExperimentalisSame topicMuscle activation and electromyography studiesFrench-language works237,207