Is there an association between proficiency in fundamental movement skills and moderate‐to‐vigorous physical activity in childhood on weekdays and weekends? The <scp>REACT</scp> project
Bibliographic record
Abstract
OBJECTIVE: The present study probes into the association between children's fundamental movement skills (FMS) and moderate-to-vigorous physical activity (MVPA) during weekdays and weekends. METHODS: This cross-sectional sample included 1014 children aged 6-10 years from the REACT project. Physical activity was assessed with accelerometry, and five FMS (stationary dribble, kick, catch, overhand throw, and underhand roll) were assessed with the digital platform Meu Educativo®. Three groups were formed based on the frequency of FMS that each child mastered: group 1 (wizard level in four or five FMS); group 2 (wizard level in two or three FMS); and group 3 (wizard level in at most one skill). Multilevel models were used to analyze the data treating children (level-1) nested within schools (level-2). RESULTS: ), independent of age and sex. There was a decline in MVPA during the weekend. Further, on average, boys were more active than girls, and with increasing age, children were less active. CONCLUSION: On average, children with higher FMS levels are generally more physically active than their peers with lower FMS levels. Even though MVPA tends to decline on weekends, FMS proficiency is a significant factor in maintaining 60 min of MVPA on weekends.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".