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Development of hand function among children with cerebral palsy: growth curve analysis for ages 16 to 70 months

2003· article· en· W4232810898 on OpenAlexafffund
Steven Hanna, Mary Law, Peter Rosenbaum, Gillian King, Stephen D. Walter, Nancy Pollock, Dianne J Russell

Bibliographic record

VenueDevelopmental Medicine & Child Neurology · 2003
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsMcMaster University Medical CentreThames Valley Children's CentreMcMaster University
FundersCanada Research ChairsOntario Ministry of Health and Long-Term Care
KeywordsCerebral palsyMedicineUpper limbPopulationPhysical medicine and rehabilitationPhysical therapyPediatricsPsychology

Abstract

fetched live from OpenAlex

This study documents the development of hand and upper‐extremity function in young children who have cerebral palsy (CP) with upper‐extremity involvement using longitudinal data. Assessments of hand function and the quality of upper‐extremity movement were conducted on 29 males and 22 females (mean age 36.2 months, SD 10.6; age range 16 to 60 months at baseline) and on four other occasions over 10 months. Linear mixed effects modeling was used to estimate average developmental curves and the degree of individual differences in the patterns of development which were conditional on the body‐site distribution of CP and severity of impairments. Results indicate that hand function in this clinical population develops differently from overall upper‐extremity skills with declines in function in upper‐extremity skills being more common and pronounced among older children. However, there is substantial interindividual variation. Distribution of CP and severity of impairments were significant predictors of development. Results are discussed in terms of their clinical implications.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.012
GPT teacher head0.233
Teacher spread0.221 · 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 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

Citations50
Published2003
Admission routes2
Has abstractyes

Explore more

Same venueDevelopmental Medicine & Child NeurologySame topicCerebral Palsy and Movement DisordersFrench-language works237,207