Characteristics of children's physical activity during active play
Bibliographic record
Abstract
BACKGROUND: Emerging evidence suggests that oxygen consumption (VO2) for self-paced physical activity (PA) is underestimated when applying laboratory-based treadmill (TM)-derived regression equations. This study examines the accelerometer (ACC) characteristics for paced TM PA and self-paced children's PA to ascertain if the predictable regulated patterns of paced PA are implicated in the inferior estimates of VO2. METHODS: Children's (9.3±1.2 years) (N.=21) VO2 (portable oxygen analyzer) and PA (accelerometry) were measured for paced treadmill PA (4-10 km/h). Active playing of children's games in a camp setting was used for self-paced PA. Treadmill and self-paced PA were compared by linear regression and Bland-Altman analysis. Relative contribution of each axes (% axis difference) for paced and self-paced PA were assessed (N.=21). RESULTS: The VO2 responses during paced treadmill exercise was linear with ACC quantified PA (for vertical axis r=0.95±0.03 and for vector magnitude [VM] r=0.95±0.05, P>0.05). During self-paced PA, the VO2 responses for ACC quantified PA were not linear (for vertical axis r=0.20±0.11 and for VM r=0.25±0.09) over the same range of ACC PA (0-1500 counts/10 s). VO2 estimates for self-paced PA (using TM-derived equations) were underestimated (P<0.05) across the range of intensities, which increased as the intensity of PA increased (>6 METs). Comparing paced versus self-paced PA the % axis dominance (i.e., difference between the highest and lowest axis) contribution to PA was 41±14% for paced and 3±2% for self-paced PA (P<0.05). CONCLUSIONS: This study reveals that the inferior estimates of VO2 for self-paced PA (using-derived linear equations) is attributable to the presence of a dominant axis with paced TM PA, which inflates the calculation of VM and the predicted VO2 for self-paced PA where no % axis difference exists.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".