Reproducibility of a Laboratory Based 20-km Time Trial Evaluation in Competitive Cyclists Using the Velotron Pro Ergometer
Bibliographic record
Abstract
The purpose of this study was to evaluate the reliability of a 20-km cycling time trial using the Velotron cycle ergometer in competitive cyclists. Twenty male cyclists (V.O (2max) = 68.5 +/- 3.6 ml . kg (-1) . min (-1); peak power (P (peak)) = 469 +/- 33 W) participated in this study. Each subject performed a V.O (2max) test and 3 separate 20-km time trials (TT1, TT2, and TT3). Data from trials were compared using a one-way ANOVA. Coefficients of variation (CV) and 95 % confidence intervals (CI) were calculated between trials. Values are mean +/- SD unless otherwise noted. Performance time T (tot) (30.03 +/- 1.24, 30.12 +/- 1.21, and 30.14 +/- 1.21 min) and mean absolute power (P (mean)) (326 +/- 35, 323 +/- 35, 322 +/- 34 Watts) were not significantly different across TT1 - TT3. P (mean) was highly related between TT1 - TT2 (r = 0.96; p < 0.01) and TT2 - TT3 (r = 0.97; p < 0.01). A low CV was also demonstrated between trials for P (mean) (TT1 - TT2 = 2.1 %, CI = 1.6 % to 3.1 %; TT2 - TT3 = 1.9 %, CI = 1.4 % to 2.8 %). P (peak) and P (mean) were both correlated to T (tot) in TT1 with P (mean) accounting for most of the variance in T (tot) (R (2) = 0.993). These data show that performance in a 20-km time trial using the Velotron ergometer is highly reproducible in competitive cyclists. Furthermore, the CV variance demonstrated between trials is comparable to that expected during actual performance in elite athletes.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".