Physiological assessment of a 16 day, 4385 km ultra‐endurance mountain bike race: A case study
Bibliographic record
Abstract
Abstract The Tour Divide (TD) is a 4385 km ultra‐endurance bicycle race that follows the continental divide from Canada to Mexico. In this case study, we performed a comprehensive molecular and physiological profile before and after the completion of the TD. Assessments were performed 35 days before the start (Pre‐TD) and ∼36 h after the finish (Post‐TD). Total energy expenditure was assessed during the first 9 days by doubly labelled water (2H218O), abdominal and leg tissue volumes via MRI, and graded exercise tests to quantify fitness and substrate preference. Vastus lateralis muscle biopsies were taken to measure mitochondrial function via respirometry, and vascular function was assessed using Doppler ultrasound. The 47‐year‐old male subject took 16 days 7 h 45 min to complete the route. He rode an average of 16.8 h/day. Neither maximal O2 uptake nor maximal power output changed pre‐ to post‐TD. Measurement of total energy expenditure and dietary recall records suggested maintenance of energy balance, which was supported by the lack of change in body weight. The subject lost both appendicular and trunk fat mass and gained leg lean mass pre‐ to post‐TD. Skeletal muscle mitochondrial and vascular endothelial function decreased pre‐ to post‐TD. Overall, exercise performance was maintained despite reductions in muscle mitochondrial and vascular endothelial function post‐TD, suggesting a metabolic reserve in our highly trained athlete.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".