Effect of walking, running, and an end-task on object circumvention direction in soccer players and non-athletes
Bibliographic record
Abstract
Object avoidance strategies are dictated by the layout of the environment. Little research has examined obstacle avoidance at varying speeds and with the inclusion of an end-task. The purpose of this study was to examine the effects of sport-specific training, locomotion speed, and an end-task on single obstacle circumvention direction. Participants (varsity soccer players, n=10 and gender matched non-athletes, n=10) travelled along a 13m pathway towards a goal marked on the floor and avoided a single obstacle placed in one of three medio-lateral locations: middle, 20cm left of middle (left), and 20cm right of middle (right). Participants completed four trials per obstacle location during four conditions: 1) walking; 2) running; 3) walking with an end-task (walk+kick); and 4) running with an end-task (run+kick). During the end-task conditions, a soccer ball was placed on the goal and was kicked at the wall with the inside of either foot. Results revealed that soccer players and non-athletes both avoided the obstacle toward the side that afforded more space and circumvented to the right more frequently when the obstacle was in the middle location. During the walk+kick condition, non-athletes avoided the obstacle to the right more often than soccer players (p<0.05) while during the run+kick condition both groups avoided to the right more often, regardless of obstacle location. It appears soccer players’ direction of circumvention was most affected by the inclusion of an end-task and speed increase. When soccer players moved at speeds different from training, environmental cues dictated the direction of avoidance rather than the end-task. When performing faster, more familiar speeds, soccer players used end-state body orientation for kicking to dictate the direction of avoidance. Conversely, non-athletes performed uniformly across the end-task conditions, indicating that neither changes in approach speed, nor an end-task, have an effect on avoidance direction for this cohort. Meeting abstract presented at VSS 2013
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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) | 0.000 | 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) | 0.002 | 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".