Reliability Study of the Items of the Alberta Infant Motor Scale (AIMS) Using Kappa Analysis
Bibliographic record
Abstract
PURPOSE: We evaluated the interrater and intrarater reliabilities of the Korean version of the Alberta Infant Motor Scale (K-AIMS). METHODS: For the interrater reliability test, six raters participated in the K-AIMS evaluation using video clips of 70 infants (aged between 0 and 18 months). One rater participated in an intrarater reliability test. Among 70 infants, 46 were born preterm and 24 were born full term. A total of 58 AIMS items were evaluated for supine, prone, sitting, and standing positions. A reliability analysis was conducted using ICC and Fleiss' kappa. RESULTS: The highest Fleiss' kappa was found for the 4-7 months group for sitting (K = 0.701-1.000) and standing (K = 0.721-1.000), while the lowest K was the 3 months or under group for standing (K = 0.153-1.000). We found higher Fleiss' kappa statistics when all infants were evaluated without grouping for the three positions (K = 0.727-1.000), except standing (K = 0.192-1.000), for the interrater analysis. CONCLUSION: Our results demonstrate the good reliability for the Korean version of the AIMS for Korean infants (preterm and full term).
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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 | 0.040 | 0.094 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".