DIFFERENCES BETWEEN EXPERT AND NOVICE GYMNASTS PERFORMANCE OF A COUNTER MOVEMENT FORWARD IN FLIGHT ON UNEVEN BARS
Bibliographic record
Abstract
This study investigated the different strategies exhibited by expert and novice gymnasts in counter movement forward in flight on uneven bars. Eleven gymnasts performed three trials connected with a kip to support. The gymnasts were divided into two groups according to their ability to connect: six able (termed as experts) versus five non-able (novices). The 3D motion data were collected at 250 Hz. Biomechanical parameters were computed at release (release state and angular momentum), during aerial phase (duration, minimum value of the moment of inertia) and at regrasp (total duration and rotation angle). Robustness of the release state was also compared. Significant differences were found between groups in the three phases. The novice gymnasts performed as robustly as expert gymnasts but less efficiently because they released the low bar before their centre of mass passed the horizontal, with a lower vertical velocity, resulting in a lower and shorter aerial phase. They also had a larger minimum moment of inertia in flight. Coaches could help novice gymnasts to decrease their dependency on their robust technique by improving the release angle. Exercises, which may allow novice gymnasts to exceed the threshold of a 90° rotation angle at release are suggested.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".