Effect of trunk stabilization on throwing velocity in heptathlon and decathlon athletes
Bibliographic record
Abstract
Title: Effect of trunk stabilization on throwing velocity in heptathlon and decathlon athletes Background: Throwing disciplines are an important part of combined track and field events. A stable trunk is a necessary component of the kinematic chain in the generation of force during throwing. Throwing is usually ineffective if the leg and trunk muscles are unable to generate sufficient force or if there is no transfer of energy to the throwing arm. This paper examines the effect of trunk stabilization on throwing velocity. Objective: The aim of the study was to investigate whether it is possible to increase the throwing velocity of heptathlon and decathlon athletes by using exercises aimed at improving trunk stabilization. Methods: Measurement of throwing velocity using sports radar, assessment of trunk stabilization level using Janda's stereotype of push-up, Kolar's bear test and deep squat test and McGillʹs torso muscular endurance test battery. Results: During the ten-week intervention focused on trunk stabilization, the experimental group experienced an average improvement in throwing velocity of 5.76 km/h (8.9%). The control group, continuing with standard training, experienced only a slight improvement in throwing velocity of 1 km/h (2%). In the evaluation of trunk stabilization, the...
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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) | 0.001 | 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) | 0.004 | 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".