MOVI-da 10! Un programa de descansos activos para mejorar la salud y favorecer los aprendizajes en Educación Infantil
Bibliographic record
Abstract
En la primera parte de este libro, se describen los antecedentes y el estado actual del tema de estudio a través de un breve resumen sobre: obesidad y sedentarismo como uno de los principales problemas de salud pública actuales; la relación entre AF, obesidad y rendimiento académico o cognitivo; así como, los últimos hallazgos relacionados con la AF integrada en el aula, destinada a mejorar la salud y el rendimiento cognitivo en la infancia. Además, en esta primera parte también se detallan los objetivos y la metodología utilizada en el estudio MOVI-da 10!. En la segunda parte, se especifican las características del programa MOVI-da 10!, y se detallan de forma reproducible 100 de las diferentes actividades utilizadas en el programa, de tal forma que puedan ser de utilidad para cualquier profesional interesado en llevar a cabo intervenciones de AF a través de descansos activos dentro del aula.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".