Critical aerobic power during simulated 20 km bicycle racing
Bibliographic record
Abstract
The main purpose of the study was to investigate the relationships between the Lactate Threshold (LT), maximal oxygen uptake (KO2max), performance time, and Critical Aerobic Power (CAP) during a simulated 20 km cycling time trial (20 kmTT). CAP was operationally defined as the average oxygen uptake sustained during the 20 kmTT. The subjects were 11 experienced male cyclists (mean±SD age: 29±7.2 yr; VO2max: 4.51±0.11 (L · min−1). Each subject completed two 20 kmTT using their own racing bicycle on a custom designed, computerized roller system. Elapsed time for the best trial averaged 34.58 ±3.29 min. Test‐retest reliability estimates for elapsed time, average heart rate and VO2 during the two trials were 0.92, 0.98 and 0.98, respectively. Oxygen uptake during the 20 kmTT averaged 115% of VO2 at LT and 86% of FO2max· A significant correlation was found between CAP and performance time (r= —0.81, p ≤ 0.01). Significant correlations were found between CAP and VO2 at LT (r = 0.62, p ≤ 0.05) and CAP and VO2max (r = 0.97, p ≤ 0.05). Using stepwise regression, VO2max was the strongest predictor of CAP with no further contribution from VO2 at LT. It was concluded that CAP is a strong determinant of cycling performance for 30–40 min duration. In this study, CAP was dependent more on VO2max than on the LT.
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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) | 0.001 | 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".