Relationship between gross motor capacity and daily‐life mobility in children with cerebral palsy
Bibliographic record
Abstract
AIM: The aim of this study was to examine the relationship between gross motor capacity and daily-life mobility in children with cerebral palsy (CP) and to explore the moderation of this relationship by the severity of CP. METHOD: Cross-sectional analysis in a cohort study with a clinic-based sample of children with CP (n=116; 76 males, 40 females; mean age 6 y 3 mo, SD 12 mo, range 4 y 8 mo-7 y 7 mo) was performed. Gross motor capacity was assessed by the Gross Motor Function Measure (GMFM-66). Daily-life mobility was assessed using the Pediatric Evaluation of Disability Inventory (PEDI): Functional Skills Scale (FSS mobility) and Caregiver Assistance Scale (CAS mobility). Severity of CP was classified by the Gross Motor Function Classification System (48% level I, 17% level II, 15% level III, 8% level IV, 12% level V), type of motor impairment (85% spastic, 12% dyskinetic, 3% ataxic), and limb distribution (36% unilateral, 49% bilateral spastic). RESULTS: Scores on the GMFM-66 explained 90% and 84% respectively, of the variance of scores on PEDI-FSS mobility and PEDI-CAS mobility. Limb distribution moderated the relationship between scores on the GMFM-66 and the PEDI-FSS mobility, revealing a weaker relationship in children with unilateral spastic CP (24% explained variance) than in children with bilateral spastic CP (91% explained variance). INTERPRETATION: In children aged 4 to 7 years with unilateral spastic CP, dissociation between gross motor capacity and daily-life mobility can be observed, just as in typically developing peers.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".