Promoting healthful diet and physical activity in the Mexican school system for the prevention of obesity in children
Bibliographic record
Abstract
Objetivo. El presente trabajo describe el protocolo, objetivo, el diseño y los métodos de un ensayo controlado aleatorio de dos años realizados para evaluar la efectividad de una intervención ambiental en 27 escuelas primarias de la Ciudad de México. Material y métodos. El protocolo consta de dos unidades de análisis: el nivel escolar donde se evaluaron los cambios en el entorno escolar de escuelas primarias publicas de medio tiempo y el nivel individual que evaluó los cambios de comportamiento en alumnos de 9 a 11 años de edad. Se implementaros dos tipos de intervenciones: nutrición y actividad física apoyadas de una estrategia de educación/comunicación. Las intervenciones tuvieron dos intensidades: básica y plus. La evaluación de la efectividad se llevó a cabo durante los ciclos escolares 2006-2007 y 2007-2008. Resultados. Los resultados iniciales reportan los métodos de evaluación de conducta individual así como la prevalencia de sobrepeso y obesidad. La evaluación ambiental reporta el protocolo de evaluación del entorno escolar. Conclusiones. Este es el primer proyecto de la de intervención escolar con un diseño multinivel, multifactorial, basado en literatura científica disponible y en investigación formativa para prevenir la obesidad infantil en las escuelas de la Ciudad de México. * * Supported by International Life Science Institute (ILSI), Pan American Health Organization (PAHO), the Mexican Council for Science and Technology (Conacyt), and Mexican Ministry of Health (SSa).
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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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".