Desarrollo motor de una cohorte retrospectiva de niños colombianos de hasta un año de edad corregida, según la escala motora infantil de Alberta
Bibliographic record
Abstract
OBJECTIVES: The Alberta Infant Motor Scale is used worldwide to assess motor development in children under 18 months of age, both preterm and full-term. In Colombia, the scale is used, but there is little information on the results it yields. The objective of this study was to characterize a retrospective cohort of children under one year of age according to the Alberta scale to generate information about the results of its application in a Colombian population treated at a highly specialized hospital. METHODS: Descriptive, retrospective, cross-sectional study, in which the medical records of 411 children with corrected age between 0 and 12 months and a history of gestational age less than 40 weeks were evaluated. The Alberta scale was applied to all children between 2010 and 2016, and scores were analyzed statistically in a descriptive form. RESULTS: Most patients were classified by the scale as "normal development" as would be expected based on their medical history. The children in our sample had lower scores than those of the original Canadian sample at all ages. CONCLUSIONS: The scale was useful for screening normal children; however, the patients had lower scores when they were evaluated by the scale than in the original study, thus making evident the need to validate the scale in Colombia and generate reference curves.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".