Validation Of An On-ice Continuous Multistage Test For Short Track Speed Skaters
Bibliographic record
Abstract
PURPOSE: There are still no sport-specific tests to evaluate directly on ice the aerobic capacity for short track speed skating athletes. The aim of this project was to create an on-ice test to estimate skater’s VO2max. METHODS: Two athletes of the men’s Canadian national team participated in the pilot study. Participants were 22 years old, with mean body weight of 69.8 ± 1.0 kg and height of 176.5 ± 8.9 cm. The skaters performed a continuous multistage test on Olympic-sized ice rink (Maurice Richard arena, 111.12m course perimeter). An audio track was created (beep test audio track) so that the speed of skating would accelerate by 0.20 seconds every 2 lap stages. The first stage started at 13.0 seconds/lap, representing a speed of 8.55 m/s. The skaters had to follow the rhythm of increasing speed until exhaustion or until they could no longer maintain the pace (off on two consecutive beeps). Measurements during the test for oxygen consummation (VO2), respiratory exchange ratio (RER) and heart rate (HR) were performed with a portable metabolic analyzer and an HR monitor. RESULTS: Skater #01 stopped at stage 15 (10.89 m/s) with an HR of 185 bpm, a VO2max of 61 ml/min/kg and a RER of 1.27., compared to skater #02 who stopped at stage 18 (11.58 m/s) with an HR of 194 bpm, a VO2max of 66 ml/min/kg and a RER of 1.28. These preliminary results suggest that the protocol brings athletes to their maximal capacity by reaching a plateau for the HR and VO2, and a RER higher than 1.15. CONCLUSIONS: A progressive speed skating test till exhaustion appears to measure maximum aerobic capacity of elite speed skaters. Nonetheless, many other data collections should be done with different levels of skaters, at different ages and gender, with the aim of creating a VO2max. estimating chart and also confirmed with a laboratory-based VO2max. measurement on cycle ergometer.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".