Physiological and Psychological Adaptations of Trained Cyclists to Spring Cycling Camps
Bibliographic record
Abstract
The purpose of our study was to assess physiological adaptations and measure mood outcomes following a cycling training camp in competitive athletes. Fourteen competitive athletes (8 males, 6 females) performed 2 incremental tests to exhaustion before and after a training camp. Volume and intensity (load) of the training regimen were recorded. Submaximal and maximal metabolic data were analysed, as well as economy variables (gross mechanical efficiency and cycling economy). Skeletal muscle adaptations were assessed using near infrared spectroscopy (NIRS). For both genders (n = 14), peak power output, peak power output-W/kg ratio and peak power output-B[La] were significantly increased (p < 0.05) after the cycling training camp (p < 0.05). Significant increases occurred for gross mechanical efficiency measured at the lactate threshold (+4.9%) and at the same precamp lactate threshold power output (+2.9%). At the lactate threshold and Post Camp Lactate Threshold Power, cycling economy increased by 5.2 and 2.9%, respectively (p < 0.05). These power measurements were significantly correlated with individual fluctuations in deoxyhaemoglobin in the vastus lateralis for male cyclists only. Profile of Mood State questionnaire results showed that subcategories "Tension-Anxiety", "Confusion", "Fatigue" and "Total Global Score" significantly decreased after the training camp. Cycling training camps were associated with positive adaptations (increased cycling economy, gross mechanical efficiency and power output) as well as some mental benefits. This indicates that despite some significant physiological adaptations participants probably did not overreach during their CTC.
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 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".