MétaCan
Menu
Back to cohort
Record W633044809 · doi:10.1017/cbo9781139012942

Rehabilitation in Movement Disorders

2013· book· en· W633044809 on OpenAlexaff
Robert Iansek

Bibliographic record

VenueCambridge University Press eBooks · 2013
Typebook
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsKingston Health Sciences Centre
Fundersnot available
KeywordsRehabilitationMovement disordersPsychological interventionDystoniaPhysical medicine and rehabilitationCerebral palsyMedicineHealth carePopulationDiseasePsychologyPhysical therapyNursingPsychiatryPathologyPolitical science

Abstract

fetched live from OpenAlex

Movement disorders affect a growing patient population, but providing comprehensive care is extremely difficult. Several of these conditions are progressive and incurable; the basal ganglia has a complex role in movement control, with many potential malfunctions. This book focuses on rehabilitation approaches that have been developed and utilized internationally in an attempt to minimize impairment and maximize participation amongst these patients. Each chapter is written by movement disorder experts, rehabilitation specialists and health care professionals, giving a broad overview of current interventions and emphasizing the need for interdisciplinary management, focussing on deliverable outcomes. Common conditions such as Parkinson's disease, cerebral palsy, dystonia and Huntington's disease are comprehensively covered. This book gives neurologists, geriatricians and rehabilitation specialists an up-to-date, theoretically-based approach to managing movement disorders related to basal ganglia malfunction. Also valuable for physiotherapists, occupational therapists, speech pathologists, nurses and social workers seeking to develop and plan appropriate interventions.

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)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.044
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0440.021

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 head0.010
GPT teacher head0.206
Teacher spread0.196 · 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
GenreOther

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

Citations37
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueCambridge University Press eBooksSame topicCerebral Palsy and Movement DisordersFrench-language works237,207