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Record W2168639613 · doi:10.1123/mcj.13.4.387

Muscle Activation Patterns and Postural Control Following Stroke

2009· review· en· W2168639613 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMotor Control · 2009
Typereview
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsUniversity of British Columbia
FundersHeart and Stroke Foundation of Canada
KeywordsPhysical medicine and rehabilitationStroke (engine)Balance (ability)Motor controlMedicineMotor impairmentPsychologyNeuroscience

Abstract

fetched live from OpenAlex

Many stroke survivors have residual sensorimotor deficits that impact negatively on balance and quality of life. The purpose of this review is to provide an overview of the impairments in motor control following stroke and the impact of those impairments on muscle activation patterns during postural control in stroke. Motor control impairments following stroke result in force production that is slow, weak and lacking in precision making it difficult to produce a fast rate of force development with sufficient magnitude to be effective for postural responses. Whether postural perturbations require feedback or feedforward responses, there is impairment to the timing, magnitude and sequencing of muscle activation following stroke. The impairment in muscle activation is dependent on the extent of the motor control impairments and strategies used by the individuals following stroke to compensate for the impairments. The central nervous system uses a variety of mechanisms to improve the muscle activation patterns needed for the recovery of postural responses following stroke.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
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 head0.017
GPT teacher head0.298
Teacher spread0.281 · 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