The validity of the VO<sub>2</sub> Master Pro for measuring oxygen consumption during sedentary activity and treadmill walking and jogging
Bibliographic record
Abstract
Metabolic carts are commonly used to estimate oxygen consumption (V̇O2) during exercise, but are largely limited to controlled laboratory settings. The V̇O2 Master Pro (VMP) is a newer, portable metabolic analyzer designed to address this limitation; however, few studies have evaluated the validity of this device at varying activity levels. This study aimed to assess the validity of the VMP in measuring V̇O2 compared with a stationary metabolic cart, the COSMED Quark CPET (CQ), during sedentary activity and treadmill walking/jogging in a laboratory setting. Twenty-seven healthy adults (mean age = 22.1 ± 7.6 years; female = 51.8%) participated in two laboratory trials on separate days. In a counterbalanced order, participants used the CQ and VMP during 10 min conditions of the following activities: sedentary activity (sitting quietly), slow walking (3.2 km/h), brisk walking (5.6 km/h), and jogging (7.2 km/h). The agreement between the two measures was evaluated using equivalence testing, mean absolute percentage error (MAPE), percentage bias, intraclass correlation coefficients (ICCs), and Bland–Altman analyses. The devices showed low agreement and significant proportional biases across all activity levels (ICCs = 0.135–0.323). Equivalence testing did not demonstrate statistically significant equivalence between the devices ( p > 0.05), with the VMP underestimating V̇O2. The smallest error appeared during jogging (MAPE = 20.05%; percentage bias= −19.29%). The VMP underestimated V̇O2 at all tested intensities, demonstrating low accuracy and agreement relative to the reference measure. This may be attributed to limited ventilatory flow capture or sensor responsiveness during submaximal activities. Observed bias and within-subject variability suggest caution when using the VMP across different submaximal activity levels.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".