Comparison of lumbar force between pubertal and post-pubertal adolescents: interference of physical growth, body fat and lifestyle.
Bibliographic record
Abstract
Abstract Aim: To compare performance in the lumbar force test in pubertal and post-pubertal adolescents by controlling the interference of physical growth, body fat, screen time and physical activity. Methods: A cross-sectional study with 933 adolescents (492 girls) aged 14-19 from the city of São José, Brazil. Lumbar strength was assessed using the isometric lumbar extension test proposed by the Canadian Society of Exercise Physiology. Sexual maturation was classified according to Tanner’s criteria. Physical growth variables (age, body weight, stature, BMI), body fat (triceps and subscapular skinfolds), sedentary behavior based on screen time and overall physical activity were controlled in the Analysis of Covariance (ANCOVA), with a significance level of 5%. Results: Post-pubertal boys presented higher lumbar force compared to pubertal ones only when interference of BMI, body fat, screen time and physical activity was controlled. Pubertal girls presented higher lumbar force compared to post-pubertal ones, both when controlling the analysis for the studied variables and when not controlled by them. Conclusion: BMI, body fat, screen time and physical activity interfere in the difference in lumbar strength of boys, in which post-pubertal boys presented better performance in lumbar force compared to pubertal ones. Regardless of interference or not of these variables, pubertal girls presented better performance in lumbar force when compared to post-pubertal ones.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".