Plantar Stress-Related Injuries in Male Basketball Players: Variations on Plantar Loads during Different Maximum-Effort Maneuvers
Bibliographic record
Abstract
This study aims to compare the insole load of three maximum-effort cutting tasks in basketball. Sixteen male basketball players were recruited to participate in the study. The Pedar Mobile system was used to record the insole plantar load distribution during three cutting tasks (45° cutting, 90° cutting, and sideward cutting). The peak pressures (PP) and maximum force (MF) at the total foot and at each foot mask were used in data analysis. ANOVA with repeated measures was employed to investigate the differences in the measures among these cutting tasks. At the total foot, the highest MF value was showed when performing sideward cutting. At the heel, the highest PP and MF were found when performing 90° cutting. The PP and MF were lower when performing 90° cutting than when conducting 45° and sideward cuttings at the medial midfoot and the central forefoot. Furthermore, the MF value was lower when performing 45° cutting than when conducting sideward cutting at the medial midfoot and the central forefoot. These findings corroborate the fact that plantar loads differed during the three maximum-effort cutting maneuvers. Differences in the plantar loads for different cutting may be potential risks for overuse-related injuries to the lower extremities of basketball players.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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".