Mechanical efficiency in children with different body weight: a longitudinal assessment of the quality cohort
Bibliographic record
Abstract
Net mechanical efficiency (MEnet), which reflects the body's ability to transfer energy above resting levels in external work, is similar in young children regardless of their body weights. However, it is unclear whether MEnet remains stable during growth and maturation. We sought to determine whether net mechanical efficiency (MEnet) changes over a period of 3 years in children and to identify the factors associated with possible changes. A total of 169 children participating in the QUALITY (Quebec Adipose and Lifestyle InvesTigation in Youth) cohort completed an incremental cycling test, resulting in the same maximal power output during both visits. For MEnet, resting energy consumption was subtracted from total energy consumption at each exercise stage. Physical activity was measured using an accelerometer worn for 7 days. Participants were measured at year one and again two years later. MEnet did not differ across the visits at the 25, 50 and 75 watt stages. However, the participants exhibited lower MEnet values at follow-up for the 100 and 125 W stages (23(3) vs. 20(1)%; 25(4) vs. 20(2)%; p<0.01). Declines in MEnet correlated positively with declines in moderate-to-vigorous physical activity levels (r=0.78, p<0.05). The declines in moderate-to-vigorous physical activity levels across the visits were identified as significant predictors of MEnet changes at 100 and 125 W over 3 years, accounting for 22% of the relationship. In children, MEnet, determined at high exercise intensity, decreases within a period of three years, and the decrement appeared to be related to moderate-to-vigorous physical activity.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".