Identification of critical traction values for maximum athletic performance
Why this work is in the frame
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Bibliographic record
Abstract
The purpose of this study was to investigate the relationship between mechanically available footwear traction and performance in top-speed curved sprint running and maximum effort linear acceleration. Based on results from previous studies, it was hypothesized that performance would increase as available traction increased but only to a point after which performance would plateau and further increases in available traction would not affect performance. The goal of this study was to identify such critical traction values. Thirty-two recreational athletes performed maximum effort 2.3 m radius curve sprints and linear accelerations from a standing start using four identical mid-cut basketball shoes differing only in outsole traction. Available traction was modified by manipulating the outsole material. The traction coefficients of the test shoes, quantified with a portable traction tester on the actual test surface, were 0.26, 0.54, 0.82 and 1.13. Ground reaction forces and three-dimensional kinematics were quantified during the tests. Greater amounts of traction (both peak and average) were utilized as the mechanically available traction increased. Increases in available traction from 0.26 to 0.54 to 0.82 provided systematic performance advantages for both curved sprinting and linear acceleration. However, no further performance enhancements were detected when the available traction increased beyond 0.82. Increases in the use of available traction beyond a threshold of 0.82 were reflected in the peak but not the average utilized traction or overall ground reaction impulse generation.
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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 | 0.000 | 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 it