Objective and subjective analysis of the training content in young cyclists
Bibliographic record
Abstract
The purpose of this study was to analyse the objective and subjective training for young cyclists that is prescribed by their coaches. Seven cyclists performed an incremental exercise to exhaustion before and after 14 weeks of training using an incremental test to determine their maximal oxygen uptake (VO(2) (max)), the velocity associated with VO(2) (max) (vVO(2) (max)), and the velocity associated with the ventilatory threshold (vVT). Cyclists completed a training record with the actual content and the perceived exertion of each training session during these 14 weeks. We have focused on the actual content of the training prescribed by the coaches. Analysis of the content of each session allowed us to calculate the objective training load (volume at different intensities) and to determine the subjective training load from perceived exertion ratings (training load, monotony, strain, and fitness-fatigue). The results showed that cyclists were training at a relatively low intensity and that training rating of perceived exhaustion was weak. Moreover, after 14 weeks of training, VO2 max did not change whereas vVO(2) (max) and vVT increased significantly. Therefore, a discrepancy may exist between what is perceived during training and the effects of training. Consequently, objective and subjective indices collected from training books provided useful information supplementary to that recorded from the physiological indices alone.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".