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Record W2021036841 · doi:10.1016/s1013-7025(09)70052-1

New Approaches to Enhance Motor Function of the Upper Limb in Patients with Hemiparesis

2005· article· en· W2021036841 on OpenAlexaff
Mindy F. Levin, Nadine K. Musampa, Amy Henderson, Luiz Alberto Manfré Knaut

Bibliographic record

VenueHong Kong Physiotherapy Journal · 2005
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsUniversité de MontréalMcGill University
Fundersnot available
KeywordsHemiparesisPhysical medicine and rehabilitationMedicineRehabilitationNeuroplasticityFunctional movementStroke (engine)Compensation (psychology)Cerebral palsyPhysical therapyPsychologySurgery

Abstract

fetched live from OpenAlex

A common finding in patients with hemiparesis due to stroke is that they may use altered movement strategies to perform functional arm and hand movements. Altered movement strategies may be considered compensatory if they substitute the movements that are impaired at the behavioural level and yet lead to the accomplishment of the task at the functional level. Motor compensation may be maladaptive in that it may limit recovery of pre-morbid movement patterns. Studies in patients with stroke suggest that, given optimal training strategies and environments, behavioural recovery (re-appearance of pre-morbid movement patterns) may occur even in patients with chronic hemiparesis. On the other hand, it has also been shown that non-guided therapy may lead to the reinforcement of compensatory movements. The challenge facing rehabilitation professionals is to create optimal training environments based on current notions of plasticity and re-organisation in the central nervous system to maximise behavioural and functional recovery.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.225

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.014
GPT teacher head0.252
Teacher spread0.238 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations8
Published2005
Admission routes1
Has abstractyes

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