Impact of wearing a surgical and cloth mask during cycle exercise
Bibliographic record
Abstract
We sought to determine the impact of wearing cloth or surgical masks on the cardiopulmonary responses to moderate-intensity exercise. Twelve subjects (n = 5 females) completed three, 8-min cycling trials while breathing through a non-rebreathing valve (laboratory control), cloth, or surgical mask. Heart rate (HR), oxyhemoglobin saturation (SpO2), breathing frequency, mouth pressure, partial pressure of end-tidal carbon dioxide (PetCO2) and oxygen (PetO2), dyspnea were measured throughout exercise. A subset of n = 6 subjects completed an additional exercise bout without a mask (ecological control). There were no differences in breathing frequency, HR or SpO2 across conditions (all p > 0.05). Compared with the laboratory control (4.7 ± 0.9 cmH2O [mean ± SD]), mouth pressure swings were smaller with the surgical mask (0.9 ± 0.7; p < 0.0001), but similar with the cloth mask (3.6 ± 4.8 cmH2O; p = 0.66). Wearing a cloth mask decreased PetO2 (−3.5 ± 3.7 mm Hg) and increased PetCO2 (+2.0 ± 1.3 mm Hg) relative to the ecological control (both p < 0.05). There were no differences in end-tidal gases between mask conditions and laboratory control (both p > 0.05). Dyspnea was similar between the control conditions and the surgical mask (p > 0.05) but was greater with the cloth mask compared with laboratory (+0.9 ± 1.2) and ecological (+1.5 ± 1.3) control conditions (both p < 0.05). Wearing a mask during short-term moderate-intensity exercise may increase dyspnea but has minimal impact on the cardiopulmonary response. Novelty: Wearing surgical or cloth masks during exercise has no impact on breathing frequency, tidal volume, oxygenation, and heart rate However, there are some changes in inspired and expired gas fractions that are physiologically irrelevant. In young healthy individuals, wearing surgical or cloth masks during submaximal exercise has few physiological consequences.
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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) | 0.002 | 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".