Intraday Variation of Ankle Dorsiflexion in Short-Track Speed Skaters
Bibliographic record
Abstract
PURPOSE: Optimal ankle dorsiflexion range of motion plays a vital role in attaining the essential crouched posture necessary for excelling in speed skating. The purpose of this study was to determine how the ankle dorsiflexion angle evolves throughout a day of training and to identify the factors that influence this angle. METHODS: Thirty short-track speed skaters, from 2 teams, participated in this study. The maximum ankle dorsiflexion angle was obtained in a lunge position facing a wall, using a digital inclinometer. All measures were obtained 3 times per side, 6 times per day, on 2 training days separated by at least a week. We conducted multiple tests to study the impact of repetition, day, side, team level, sex, and moment on the ankle dorsiflexion angle. RESULTS: The 3 times repeated measures and the 2 days of training did not have a significant influence on the results. There was a statistically significant difference between the first time point of the day and the 5 other time points for both ankles. Moreover, the influence of sex and team level was not statistically significant. CONCLUSIONS: The results indicate that there are significant changes in ankle dorsiflexion range of motion but only after the first warm-up of the day. Such findings could enable team staff to enhance athletes' precompetition preparation and tailor ankle mobility training regimens more effectively.
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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 | 0.001 | 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 | 0.001 |
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".