Mudanças antropométricas e habilidade motora em crianças no início da marcha independente Anthropometrical changes and motor skill in infants at the onset of independent walking
Bibliographic record
Abstract
Changes in infants’ body dimensions occurring during development may impose specific motor demands at the onset of independent walking. That is, anthropometric features may influence infants’ gross motor performance. This study aimed at assessing the association between weight, height, and body mass index (BMI) with motor performance of typically developing infants, comparing two groups of infants with different BMI values in regard to motor performance. Weight, height, and BMI measures of 10 infants were obtained during the week of onset of independent walking. Motor performance of all infants was assessed by the Alberta Infant Motor Scale (AIMS) one week later. Results show significant correlations between BMI and motor performance (r= -0.850; p=0,002) and between weight and motor performance (r= -0.701; p= 0.024). The correlation between height and motor performance was not significant (r= -0.495; p=0.145). The two groups of infants separated by the median value of the BMI distribution showed significant differences in gross motor performance (t=3.795; p=0.005), the group with higher BMI showing lower AIMS scores. These results suggest that anthropometric features are associated with gross motor performance in infants at early stages of independent walking.
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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 | 0.000 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".