V˙O2max and the kinetics of V˙O2, muscle oxygen delivery, and muscle deoxygenation
Bibliographic record
Abstract
Introduction Aerobic fitness and oxygen uptake kinetics (τ V ˙ O 2 ) at the onset of exercise appear to be inversely correlated, however, the mechanisms underlying changes in τ V ˙ O 2 across different levels of aerobic fitness have not been elucidated. The purpose of this study was to investigate the relationship between maximal V ˙ O 2 ( V ˙ O 2max ) and τ V ˙ O 2 and determine whether the capacity to deliver or to utilize O 2 limits τ V ˙ O 2 in an aerobic fitness dependent manner. Methods Twenty-three healthy, young males (25 ± 4 years) with a V ˙ O 2max classified as superior (S; V ˙ O 2max > 60 mL · kg −1 · min −1 , n = 7), good (G; V ˙ O 2max = 45-55 mL · kg −1 · min −1 , n = 8) or poor (P; V ˙ O 2max < 40 mL · kg −1 · min −1 , n = 8) performed two moderate-intensity knee-extension (KE) exercise transitions (80% of gas exchange threshold) on a custom-built KE ergometer. V ˙ O 2 was measured breath-by-breath. Leg blood flow (BF) was measured by doppler ultrasound at the femoral artery, and leg vascular conductance (LVC) was calculated as BF·mean arterial pressure (MAP) −1 . Near-infrared spectroscopy derived-[HHb] was measured on the vastus lateralis muscle. τ V ˙ O 2 , τLVC, and τ[HHb] data were averaged and fit with a mono-exponential function. Results τ V
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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".