Influência de determinantes socioeconômicos no desenvolvimento motor de lactentes acompanhados por programa de follow-up em Manaus, Amazonas
Bibliographic record
Abstract
Child development is a gradual and continuous process divided into stages for theoretical purposes. Intrinsic and extrinsic factors can positively or negatively influence the evolution of the infant. The objective was to evaluate the influence of maternal higher education and family income on the Motor Development (MD) of infants. It was a cross-sectional study that evaluated 106 children from the follow-up program of a reference maternity hospital in Amazonas. Two questionnaires were applied (anamnesis script and socioeconomic profile); and then Alberta Infant Motor Scale to assess the MD of those infants. For statistical analysis, descriptive data and Chi-square and Fisher’s exact tests were used, with p ≤ 0.05. The higher level of maternal education was related to the typicality of MD (71.4%, with p = 0.04), on the other hand, a lower family income, despite having presented a higher percentage in atypical children (51.9%), did not demonstrate a significant relationship with MD atypicality. It was observed that, in our sample, maternal schooling had a greater impact on adequate MD when compared to family income. This fact seems to be related to the higher level of maternal education, which implies better child care, in the face of general care and stimulation.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".