Rate dependent influence of arterial desaturation on self-selected exercise intensity during cycling
Bibliographic record
Abstract
The purpose of this study was to clarify if Ratings of Perceived Exertion (RPE) and self-selected exercise intensity are sensitive not only to alterations in the absolute level of arterial saturation (SPO2) but also the rate of change in SPO2. Twelve healthy participants (31.6 ± 3.9 y, 175.5 ± 7.7 cm, 73.3 ± 10.3 kg, 51 ± 7 mL·kg-1·min-1 [Formula: see text]) exercised four times on a cycle ergometer, freely adjusting power output (PO) to maintain RPE at 5 on Borg's 10-point scale with no external feedback to indicate their exercise intensity. The fraction of inspired oxygen (FIO2) was reduced during three of those trials such that SPO2 decreased during exercise from starting values (>98%) to 70%. These trials were differentiated by the time over which the desaturation occurred: 3.9 ± 1.4 min, -8.7 ± 4.2%•min-1 (FAST), 11.0 ± 3.7 min, -2.8 ± 1.3%•min-1 (MED), and 19.5 ± 5.8 min, -1.5 ± 0.8%•min-1 (SLOW) (P < 0.001). Compared to stable PO throughout the control condition (no SPO2 manipulation), PO significantly decreased across the experimental conditions (FAST = 2.8 ± 2.1 W•% SPO2-1; MED = 2.5 ± 1.8 W•% SPO2-1; SLOW = 1.8 ± 1.6 W•% SPO2-1; P < 0.001). The rates of decline in PO during FAST and MED were similar, with both greater than SLOW. Our results confirm that decreases in absolute SPO2 impair exercise performance and that a faster rate of oxygen desaturation magnifies that impairment.
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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 | 0.002 |
| 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 | 0.000 | 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".