Peak oxygen uptake in a sprint interval testing protocol vs. maximal oxygen uptake in an incremental testing protocol and their relationship with cross-country mountain biking performance
Bibliographic record
Abstract
In the literature, the exercise capacity of cyclists is typically assessed using incremental and endurance exercise tests. The aim of the present study was to confirm whether peak oxygen uptake (V̇O2peak) attained in a sprint interval testing protocol correlates with cycling performance, and whether it corresponds to maximal oxygen uptake (V̇O2max) determined by an incremental testing protocol. A sample of 28 trained mountain bike cyclists executed 3 performance tests: (i) incremental testing protocol (ITP) in which the participant cycled to volitional exhaustion, (ii) sprint interval testing protocol (SITP) composed of four 30 s maximal intensity cycling bouts interspersed with 90 s recovery periods, (iii) competition in a simulated mountain biking race. Oxygen uptake, pulmonary ventilation, work, and power output were measured during the ITP and SITP with postexercise blood lactate and hydrogen ion concentrations collected. Race times were recorded. No significant inter-individual differences were observed in regards to any of the ITP-associated variables. However, 9 individuals presented significantly increased oxygen uptake, pulmonary ventilation, and work output in the SITP compared with the remaining cyclists. In addition, in this group of 9 cyclists, oxygen uptake in SITP was significantly higher than in ITP. After the simulated race, this group of 9 cyclists achieved significantly better competition times (99.5 ± 5.2 min) than the other cyclists (110.5 ± 6.7 min). We conclude that mountain bike cyclists who demonstrate higher peak oxygen uptake in a sprint interval testing protocol than maximal oxygen uptake attained in an incremental testing protocol demonstrate superior competitive performance.
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 | 0.001 | 0.003 |
| 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 | 0.001 | 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".