Perfil nutricional de crianças menores de dois anos, informações sociodemográficas e estado nutricional da mãe, no município de Palmas (TO)
Bibliographic record
Abstract
The assessment of the nutritional status of children is important for monitoring the quality of life and child development, besides predicting the living conditions of the general population. The aim of this study is to evaluate the nutritional profile and associated factors in children under two years of age living in the city of Palmas (TO). This is research of a quantitative nature, of a transversal nature, operating in the descriptive classification, through a survey/survey in which it uses statistical techniques, and a research instrument (questionnaire) containing questions related to sociodemographic variables. The sample studied consisted of 109 children under two years of age in the municipality, and it was possible to evaluate the nutritional status at birth of 87 (79.80%) and current of 52 (47.70%) children. Eutrophy was the most frequent nutritional status at birth and current in the children studied. Overweight was the main anthropometric deviation/nutritional status observed in children younger than two years in the municipality. There was no significant association between the nutritional status at birth and present infant with the maternal nutritional status, and it was possible to observe a greater association with the sociodemographic characteristics. Keywords: Nutritional status. Child. Child development. Weight at birth.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".