Impacto de un programa de equitación adaptada en la actividad física y en el sueño de un grupo de niños con enfermedades raras (Impact of an adaptive riding program on the physical activity and sleep in a group of children diagnosed with rare diseases)
Bibliographic record
Abstract
El objetivo de este trabajo fue verificar el impacto de un programa de equitación adaptada en un grupo de niños con enfermedades raras y comprobar su repercusión en la actividad física y en algunos parámetros del sueño. Se realiza un diseño experimental de caso único, de reversión múltiple intrasujetos. La muestra está compuesta por cinco niños/as que presentan enfermedades de baja frecuencia. Para evaluar la actividad física y el tiempo de sueño se ha utilizado un acelerómetro triaxial. Con carácter descriptivo, a fin de valorar las características habituales del sueño se ha empleado una escala de trastornos del sueño. En términos generales se observa que la participación como usuario en sesiones de equitación adaptada supone un incremento de actividad física apreciable respecto a la actividad física media del propio usuario. No hemos encontrado una prolongación en la duración de sueño. === The aim of this work is to verify the impact of a adaptive riding program to promote physical activity and sleep in a group of children with rare diseases. A single-case, reversal and intrasubject experimental design has been implemented. The sample was composed of five children with low-frequency or undiagnosed diseases. To measure physical activity and sleep an triaxial accelerometer has been used. Additionally, a sleep disorder scale has been employed in order to assess the usual sleep characteristics. In general terms, we can point out that participating as a user in adaptive riding sessions produces an increase in daily physical activity, which is appreciable compared to the average physical activity of the user.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".