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Record W4285293138 · doi:10.1123/mc.2022-0026

Motor Control: A Conceptual Framework for Rehabilitation

2022· article· en· W4285293138 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.

Bibliographic record

VenueMotor Control · 2022
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsMcGill UniversityCentre for Interdisciplinary Research in RehabilitationJewish Rehabilitation Hospital
Fundersnot available
KeywordsNeurorehabilitationMotor controlMotor learningTerminologyCLARITYPsychologyControl (management)Cognitive psychologyRehabilitationPhysical medicine and rehabilitationComputer scienceCognitive scienceNeuroscienceArtificial intelligenceMedicine

Abstract

fetched live from OpenAlex

There is a lack of conceptual and theoretical clarity among clinicians and researchers regarding the control of motor actions based on the use of the term "motor control." It is important to differentiate control processes from observations of motor output to improve communication and to make progress in understanding motor disorders and their remediation. This article clarifies terminology related to theoretical concepts underlying the control of motor actions, emphasizing how the term "motor control" is applied in neurorehabilitation. Two major opposing theoretical frameworks are described (i.e., direct and indirect), and their strengths and pitfalls are discussed. Then, based on the proposition that sensorimotor rehabilitation should be predicated on one comprehensive theory instead of an eclectic mix of theories and models, several solutions are offered about how to address controversies in motor learning, optimality, and adaptability of movement.

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)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.737
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.258
Teacher spread0.237 · 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