Can VO <sub>2max</sub> be accurately estimated using exercise-duration based prediction equations and a nomogram?
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Bibliographic record
Abstract
Abstract Study aim : The purpose of this study was to examine a large cohort of young Canadian adults to determine if exercise time from a maximal Bruce Treadmill Protocol could accurately predict measured VO 2max values by inputting the total exercise time into prediction equations and a nomogram. Materials and methods : 550 kinesiology undergraduate student (280 male and 270 female) participants, with a mean body mass (BM) of 72.08 ± 15.05 kg, mean age of 21.16 ± 1.26 years old and mean height of 171.95 ± 10.25 cm completed a maximal graded exercise test to obtain their VO 2max (measured). Predicted VO 2max was calculated with various equations using the variable of total exercise test time. Linear regression models were created to determine how well the predicted VO2max values compared to the measured values. Results : Across all VO 2max calculation methods, males obtained higher VO2max values on both the measured (49.89 ± 9.21 mL/ kg/min) and predicted values (46.04–55.40 mL/kg/min) and exercised for a longer duration of time (14.33 minutes) compared to females (40.89 ± 7.50 mL/kg/min, 38.87–48.36 mL/kg/min, 11.92 minutes). Classifications and percentile rankings were created using each measured and predicted method. Conclusions : The Healthy Persons Equation [6], Healthy Men and Women Equation [2], Active and Sedentary Women/Men Equations [10, 22] and nomogram [13] cannot accurately predict VO 2max in healthy young adults, with R 2 values between 0.38–0.50. The Healthy Persons Equation [6] was found to very closely mimic the seven-category classifications determined from the measured CPET VO2max values.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it