Inter-Rater Reliability of the Polish Version of the Alberta Infant Motor Scale in Children with Heart Disease
Bibliographic record
Abstract
There is an urgent need for the systematic monitoring of motor and cognitive neurodevelopment and the evaluation of motor skill development in infants and children with heart disease. Familiarizing students and early graduates with the developmental care needed by these patients may help in the system-wide implementation of early motor screening in this population. The purpose of this study was to investigate the agreement between a last-year physiotherapy student and an experienced pediatric physiotherapist when applying the Polish version of the Alberta Infant Motor Scale (AIMS) to a heterogenous group of children with congenital heart defects. Agreement between raters was verified based on the observation of 80 (38 females) patients with heart disease aged 1-18 months using a Bland-Altman plot with limits of agreement and an intraclass correlation coefficient. The bias between raters for the total score for four age groups (0-3 months, 4-7 months, 8-11 months and 12-18 months) was between -0.17 and 0.22 (range: -0.54-0.78), and the ICC was between 0.875 and 1.000. Thus, a reliable assessment of motor development or motor skills using the Polish version of the AIMS can be performed in pediatric patients with heart defects by clinically inexperienced last-year physiotherapy students who are familiarized with the AIMS manual.
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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 | 0.042 | 0.061 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".