Seasonal changes in aerobic fitness indices in elite cyclists
Bibliographic record
Abstract
The primary purpose of this study was to compare seasonal changes in cycling gross efficiency (GE) and economy (EC) with changes in other aerobic fitness indices. The secondary aim was to assess the relationship between maximum oxygen consumption, GE, and EC among elite cyclists. The relationships of maximum oxygen consumption with GE and EC were studied in 13 cyclists (8 professional road cyclists and 5 mountain bikers). Seasonal changes in GE and EC, predicted time to exhaustion (pTE), maximum oxygen consumption, and respiratory compensation point (RCP) were examined in a subgroup of 8 subjects, before (TREST) and after (TPRECOMP) the pre-competitive winter training, and during the competitive period (TCOMP). GE and EC were assessed during a constant power test at 75% of peak power output (PPO). Significant main effect for time was found for maximum oxygen consumption (4.623 +/- 0.675, 4.879 +/- 0.727, and 5.010 +/- 0.663 L.min(-1); p = 0.028), PPO (417.8 +/- 46.5, 443.0 +/- 48.0, and 455 +/- 48 W; p < 0.001), oxygen uptake at RCP (3.866 +/- 0.793, 4.041 +/- 0.685, and 4.143 +/- 0.643 L.min(-1); p = 0.049), power output at RCP (330 +/- 64, 354 +/- 52, and 361 +/- 50 W; p < 0.001), and pTE (17 +/- 4, 30 +/- 8, and 46 +/- 17 min; p < 0.001). No significant main effect for time was found in GE (p = 0.097) or EC (p = 0.225), despite within-subject seasonal changes. No significant correlations were found between absolute maximum oxygen consumption and GE (r = -0.276; p = 0.359) or EC (r = -0.328; p = 0.272). However, cyclists with high maximum oxygen consumption values (i.e., over 80 mL.kg(-1).min(-1)), showed low efficiency rates. Despite within-subject seasonal waves in cycling efficiency, changes in GE and EC should not be expected as direct consequence of changes in other maximal and submaximal parameters of aerobic fitness (i.e., maximum oxygen consumption and RCP).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".