The Gross Motor Function Classification System for Cerebral Palsy: a study of reliability and stability over time
Bibliographic record
Abstract
Children with cerebral palsy (CP) experience a change in motor function with age and development. It is important to consider this expected change in offering a prognosis, or in assessing differences in motor function after an intervention. The Gross Motor Function Classification System for CP (GMFCS) has been developed for these purposes. This study was based on a retrospective chart review of 85 children with CP followed from < or =2 to > or =12 years of age. The GMFCS was applied to clinical notes by two blinded raters four times throughout the study. Interrater reliability was high (G=0.93). Test-retest reliability was high (G=0.79). The positive predictive value of the GMFCS at 1 to 2 years of age to predict walking by age 12 years was 0.74. The negative predictive value was 0.90. The GMFCS can validly predict motor function for children with CP. The results are discussed in terms of their implications for clinical practice and future research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.069 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".