MétaCan
Menu
Back to cohort

Stability of the Gross Motor Function Classification System

2007· article· en· W4245209743 on OpenAlexafffund
Robert J. Palisano, David Cameron, Peter Rosenbaum, Stephen D. Walter, Dianne J Russell

Bibliographic record

VenueDevelopmental Medicine & Child Neurology · 2007
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsMcMaster University
FundersNational Institutes of HealthNational Center for Medical Rehabilitation ResearchNational Institute of Child Health and Human DevelopmentMedical Research Council Canada
KeywordsStability (learning theory)Gross motor skillFunction (biology)Control theory (sociology)MathematicsArtificial intelligenceComputer scienceBiologyMachine learningNeuroscienceMotor skillControl (management)

Abstract

fetched live from OpenAlex

The aim of this study was to assess the stability of the Gross Motor Function Classification System (GMFCS) by examining whether children with cerebral palsy (CP) remain in the same level over time. Participants were 610 children with CP (342 males, 268 females; mean age 6y 9mo [SD 2y 10mo]), range 16mo-13y). Children were assessed 2 to 7 times (mean 4.3) at 6-month (children <6y old) or 12-month (children ≥6y old) intervals. Seventy-three per cent of children remained in the same level for all ratings. The weighted kappa coefficient between the first and last ratings was 0.84 for children less than 6 years old and 0.89 for children at least 6 years old, indicating excellent chance-corrected agreement. Children initially classified in Levels I and V were least likely to be reclassified. There was a tendency for children younger than 6 years who were reclassified to be done so to a lower level of ability. The results provide evidence of stability of the GMFCS.

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)0.001
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 score0.104
Threshold uncertainty score0.394

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.023
GPT teacher head0.246
Teacher spread0.224 · 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

Citations103
Published2007
Admission routes2
Has abstractyes

Explore more

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