Reference curves for the Brazilian Alberta Infant Motor Scale: percentiles for clinical description and follow-up over time
Bibliographic record
Abstract
OBJECTIVES: To compare Alberta Infant Motor Scale scores for Brazilian infants with the Canadian norm and to construct sex-specific reference curves and percentiles for motor development for a Brazilian population. METHODS: This study recruited 795 children aged 0 to 18 months from a number of different towns in Brazil. Infants were assessed by an experienced researcher in a silent room using the Alberta Infant Motor Scale. Sex-specific percentiles (P5, P10, P25, P50, P75 and P90) were calculated and analyzed for each age in months from 0 to 18 months. RESULTS: No significant differences (p > 0.05) between boys and girls were observed for the majority of ages. The exception was 14 months, where the girls scored higher for overall motor performance (p = 0.015) and had a higher development percentile (0.021). It was observed that the development curves demonstrated a tendency to nonlinear development in both sexes and for both typical and atypical children. Variation in motor acquisition was minimal at the extremes of the age range: during the first two months of life and from 15 months onwards. CONCLUSIONS: Although the Alberta Infant Motor Scale is widely used in both research and clinical practice, it has certain limitations in terms of behavioral differentiation before 2 months and after 15 months. This reduced sensitivity at the extremes of the age range may be related to the number of motor items assessed at these ages and their difficulty. It is suggested that other screening instruments be employed for children over the age of 15 months.
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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 | 0.008 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".