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Record W2324659657 · doi:10.1017/s0317167100005308

Progress in Clinical Neurosciences: Stroke Recovery and Rehabilitation

2006· review· en· W2324659657 on OpenAlexafffundvenue
Robert Teasell, Nestor A. Bayona, Katherine Salter, Chelsea Hellings, Jamie Bitensky

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2006
Typereview
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsSt Joseph's Health CareWestern University
FundersCanadian Stroke NetworkHeart and Stroke Foundation of Canada
KeywordsRehabilitationStroke (engine)Stroke recoveryNeuroplasticityPhysical medicine and rehabilitationNeuroscienceSpontaneous recoveryPsychologyMedicineLesionPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Recent literature has provided new insights into the role of rehabilitation in neurological recovery post-stroke. The present review combines results of animal and clinical research to provide a summary of published information regarding the mechanisms of neural recovery and impact of rehabilitation. METHODS: Plasticity of the uninjured and post-stroke brain is examined to provide a background for the examination of brain reorganization and recovery following stroke. SUMMARY AND CONCLUSIONS: Recent research has confirmed many of the basic underpinnings of rehabilitation and provided new insight into the role of rehabilitation in neurological recovery. Recovery post stroke is dependent upon cortical reorganization, and therefore, upon the presence of intact cortex, especially in areas adjacent to the infarct. Exposure to stimulating and complex environments and involvement in tasks or activities that are meaningful to the individual with stroke serves to increase cortical reorganization and enhance functional recovery. Additional factors associated with neurological recovery include size of stroke lesion, and the timing and intensity of therapy.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0040.004
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0070.005

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 head0.064
GPT teacher head0.368
Teacher spread0.303 · 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

Citations53
Published2006
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences NeurologiquesSame topicStroke Rehabilitation and RecoveryFrench-language works237,207