Oxygen Uptake Kinetics: Implications for Endurance Running Success
Bibliographic record
Abstract
The kinetics of oxygen uptake () reflect the rate at which the oxidative energy supply system is adapting to the demands of a new, higher, work rate. An athlete starting a 5,000 m race requires rapid adaptation of oxidative phosphorylation to minimize the contribution of phosphocreatine and anaerobic glycolysis with lactate accumulation during the period of oxygen deficit. This will enable the athlete to maintain reserves for the sprint to the finish. kinetics are affected by both the rate at which metabolic pathways are activated and the ability to transport O2 to the exercising muscles. Following the onset of moderate intensity exercise, increases in a fit athlete to attain a steady state within the first two minutes. However, for higher intensities of exercise such as 5,000 m running where the metabolic demand is approaching the attainment of a steady state is delayed. In the case of the high intensity exercise, there is a corresponding slower response of cardiac output (). Prior warm-up exercise at either moderate or heavy intensity has been shown recently to cause a more rapid increase in which then facilitates a more rapid increase in . This review highlights some of the recent evidence concerning the kinetics of and in fit, endurance-trained, athletes during moderate and heavy intensity exercise.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".