Ultrasound Measurements and Physical Fitness of Elite Youth Basketball Players
Bibliographic record
Abstract
The countermovement jump, the V-cut test, the muscle thickness and the adjacent subcutaneous fat thickness of the gastrocnemius medialis and rectus femoris are important physiological indicators for success in basketball. The aims of this study were to evaluate between-age-category and between-gender differences in these indicators and examine the relationships between physical tests and ultrasound measurements. The measurements were recorded in a sample of 131 elite basketball players (66 males) who played in three age-categories (U14, U16, or U18). We performed two-way analysis of covariance tests and age-adjusted partial correlation analyses. U16 and U18 males showed better performance in the countermovement jump and V-cut tests and lower adjacent subcutaneous fat thickness of the gastrocnemius medialis and rectus femoris compared to the U14 males (p≤.001) and to age-category equivalent female players (p≤.001). Comparisons between the age categories in females did not show significant differences in any of the study variables. Adjacent subcutaneous fat thickness of the gastrocnemius medialis explained 22.3% of the variation for the countermovement jump result and 12.9% of the variation for the V-cut result in males (p<.01). This study is the first to show the association and predictive role of subcutaneous fat thickness measured by ultrasound in physical performance of male and female elite youth basketball players.
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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 | 0.000 | 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) | 0.001 | 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".