Changes in leg kinematics in response to unpredictability in lateral jump execution
Bibliographic record
Abstract
Lateral movements like cutting are essential in many team sport disciplines. The aim of the present study was to analyse adaptations in motor control in response to task unpredictability during lateral movement execution. Twelve subjects performed lateral jumps with different landing modalities (stable, sliding or counteracting) that were either known (predictable setting) or unknown (unpredictable setting) prior to movement execution. Results revealed that regardless of the landing modality, hip joint abduction was significantly greater in the unpredictable compared to predictable setting. Furthermore, during the sliding landing modality, hip flexion decreased from 211 ± 7° to 207 ± 7° and knee flexion decreased from 26 ± 4° to 24 ± 4° at the instant of ground contact in the unpredictable compared to predictable condition. During the stable landing modality, the knee joint abduction increased from -0.3 ± 6° to -3 ± 6° after initial ground contact in the unpredictable compared to predictable setting. The present results support our hypothesis that pre-programmed motor activity depends on the predictability of the landing modality during lateral movements. According to its adaptation in the frontal plane and in some extent in the sagittal plane, the hip joint seems to play the major role in the modulation of the pre-programmed activity for successful lateral jump execution in an unpredictable setting. However, these kinematic adaptations are concerning since these changes were associated with higher knee abduction during the stable landing modality and therefore with possible higher risk of injury.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".