Commentary on “Assessing Gross Motor Development of Brazilian Infants”
Bibliographic record
Abstract
“How should I apply this information?” In general, the results showed lower scores on the Alberta Infant Motor Scale (AIMS) for Brazilian children. Because the differences were small, the AIMS may still be considered valid for use for Brazilian children. Of note are the lower scores for Brazilian children who rank in the 10th and 5th percentile categories at 4 to 5 months, and 9 to 10 months, and 10 to 11 months. Clinically, this indicates the potential for AIMS norms (established in Canada) to overidentify Brazilian infants as being at risk for later motor delays in those age groups. The use of the Brazilian reference values is recommended for Brazilian children of those age groups to avoid identifying a motor delay when there is no delay, especially for the 4- to 5-month age group where AIMS cut-off risk scores have been identified. No differences were found on the basis of the economic status, but the Brazilian sample was mostly composed of children from high–medium to high categories of the Human Development Index (statistic of life expectancy, education, and income). Infants from families with lower economic status may show different results. “What should I be mindful about in applying this information?” Because the AIMS only has cut-off risk scores at 4 and 8 months, it is difficult to determine the ability to use these data to identify Brazilian children at risk for later motor dysfunction across the entire 0- to 18-month age span. Given the lower scores of Brazilian children on the AIMS, the ability of the AIMS to identify the children with later motor dysfunction needs to be established within cultural and economic groups rather than generalized across groups. Users of the AIMS should be mindful that the “back to sleep” recommendation has resulted in a transient effect on motor development affecting mostly prone development, because many parents unnecessarily avoid prone positioning of their infants during waking hours. Yvette Blanchard, ScD, PT, PCS Sacred Heart University, Fairfield, Connecticut Gunn Kristin Øberg, PT, PhD UiT, The Arctic University of Norway, Tromsø, Norway
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".