Critical skating intensity on a slide board: physiological and neuromuscular responses and correlation with performance on ice
Bibliographic record
Abstract
The aim of this study was to assess the physiological and neuromuscular responses at critical skating intensity on a slide board and to investigate the correlations between critical cadence (CC) and skating performances on ice. Thirteen well-trained speed skaters (age,19.8 ± 4.2 years; weight, 69.6 ± 9.06 kg) performed a maximal skating incremental test (IT) on a slide board. CC was determined from 3 to 4 trials to exhaustion lasting from 3.1 ± 0.7 to 13.9 ± 3.1 min, using linear and hyperbolic mathematical fittings. A time to exhaustion test at CC (TTE-CC) was performed. CC values (55.3 ± 5.0 ppm) were significantly higher than cadence at the respiratory compensation point (RCP) (53.5 ± 4.0 ppm). Mean duration of TTE-CC was 22.9 ± 4.8 min. Peak values of oxygen uptake, heart rate (HR), ventilation, respiratory exchange ratio (RER), and ratings of perceived exertion (RPE) during TTE-CC were significantly lower (p < 0.05) than the peak values reached during the IT. Oxygen uptake, HR, ventilation, RER, and RPE significantly increased from 25% to 100% of TTE-CC. Muscle activity (integrated electromyography) significantly increased after 75% of TTE-CC for vastus lateralis and gluteus maximus muscles. Oxygen uptake at CC was better associated to skating performance on 500, 1000, 1500, and 5000 m than peak oxygen uptake at IT and oxygen uptake at RCP. Physiological responses indicate that critical skating intensity on slide board occurred within the heavy exercise domain where oxygen uptake increases but does not reach its maximum. Critical cadence could be used as a better indicator of performance and training prescription for long track speed skating distances.
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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 | 0.000 | 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".