Influence of physical development on start and countermovement jump performance in adolescent sprint athletes.
Bibliographic record
Abstract
AIM: The aim of the present study was to describe the effect of physical changes during adolescence on sprint start and countermovement jump (CMJ) performance. METHODS: Twenty-eight girls and 25 boys (15.0±1.6 and 14.7±1.9 years at start respectively) were measured twice with a one year interval. Anthropometric data allowed skeletal muscle mass (SMM) estimation. Athletes performed a 10m sprint tracked from behind by a laser sensor, with starting blocks measuring propulsion forces. CMJ's were performed on a Kistler force plate. RESULTS: Between the two measurement occasions both genders increased in body height, weight and SMM. In girls and boys, impulse during the push-off, block leaving velocity and times at 5 and 10 m improved significantly. In both genders CMJ absolute power increased but not power.kg-1. Only in boys a higher CMJ was registered on occasion 2. For both genders on both occasions, impulse during the push-off correlated with body weight, SMM and CMJ power (r from .46 to .84), and in boys also with CMJ height and CMJ power.kg-1 (r from 0.43 to 0.76). Boys showed CMJ height and power to correlate with 5 and 10 m times (r from -0.42 to -0.79) and with block leaving velocity, however only on the first data collection (r=0.61 and 0.59, respectively). CONCLUSION: Sprint start performance is only partly related to muscular development and CMJ could predict start performance in boys only. Sprint start and CMJ rely on technical skills and, therefore, increasing muscularity should be accompanied with sufficient specific training to allow an optimal transfer to start performance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".