The influence of athletic background, lower limb dominance and cutting angle on the center of mass kinematics during a sidestep cutting task
Bibliographic record
Abstract
BACKGROUND: Successful performance in futsal depends on athletes' ability to change direction efficiently. AIM: To investigate the effect of athletic background on COM kinematics during sidestep cutting maneuver performed at different cutting angles towards both sides. METHOD: Eighteen futsal athletes participated, comprised of nine high-level training (Group high-level) and nine recreational (Group Control, GC). Twenty reflective markers were placed on the participant's trunk and upper and lower limbs. Participants performed acceleration at maximum speed and in a straight line for 10 meters, followed by a change of direction (30º, 60º, and 90º). The whole body's COM trajectory was identified using a body model for each trial. Differences in angular error and COM speed were evaluated with a three-way analysis of variance [Group (GH vs. GC) X Cutting angle (30º vs. 60º vs. 90º) X Side (dominant and non-dominant), with repeated measures for the last two factors]. RESULTS: The main results indicated that the angular error increased as the cutting angle increased. The high-level futsal athletes performed a cutting task for the dominant side with greater speed and higher angular errors than the control group. These findings provided important information for understanding the trajectory of the center of mass at different angles and velocities and the possible repercussions on body dynamics. CONCLUSION: Athletic background affected the kinematic patterns of the center of mass during sidestep cutting maneuvers; when sidestep is performed with the dominant side, high-level futsal athletes changed direction faster with more significant angular error than recreational athletes.
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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".