Muscle Oxygenation Trends During Dynamic Exercise Measured by Near Infrared Spectroscopy
Bibliographic record
Abstract
During the last decade, NIRS has been used extensively to evaluate the changes in muscle oxygenation and blood volume during a variety of exercise modes. The important findings from this research are as follows: (a) There is a strong correlation between the lactate (ventilatory) threshold during incremental cycle exercise and the exaggerated reduction in muscle oxygenation measured by NIRS. (b) The delay in steady-state oxygen uptake during constant work rate exercise at intensities above the lactate/ventilatory threshold is closely related to changes in muscle oxygenation measured by NIRS. (c) The degree of muscle deoxygenation at the same absolute oxygen uptake is significantly lower in older persons compared younger persons; however, these changes are negated when muscle oxygenation is expressed relative to maximal oxygen uptake values. (d) There is no significant difference between the rate of biceps brachii and vastus lateralis deoxygenation during arm cranking and leg cycling exercise, respectively, in males and females. (e) Muscle deoxygenation trends recorded during short duration, high-intensity exercise such as the Wingate test indicate that there is a substantial degree of aerobic metabolism during such exercise. Recent studies that have used NIRS at multiple sites, such as brain and muscle tissue, provide useful information pertaining to the regional changes in oxygen availability in these tissues during dynamic 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".