Estimation of Oxygen Uptake From Heart Rate and Ratings of Perceived Exertion in Young Soccer Players
Bibliographic record
Abstract
The objective of this study was to estimate the oxygen uptake (&OV0312;O2) in elite youth soccer players using measures of heart rate (HR) and ratings of perceived exertion (RPEs). Forty-six regional-level male youth soccer players (∼13 years) participated in 2 VO(2)max tests. Data for HR, RPE, and VO(2) were simultaneously recorded during the VO(2)max tests with incremental running speed. Regression equations were derived from the first VO(2)max test. Two weeks later, all players performed the same VO(2)max test to validate the developed regression equations. There were no significant differences between the estimated values in the first test and actual values in the second test. During the continuous endurance exercise, the combination of percentage of maximal HR (%HRmax) and RPE measures gave similar estimation of %VO(2)max (R = 83%) in comparison to %HRmax alone (R = 81%). However, the estimation of VO(2) using combined %HRmax and RPE was not satisfactory (R = 45-46%). Therefore, the use of %HRmax (without RPE) to estimate %VO(2)max could be a useful tool in young soccer players during field-based continuous endurance testing and training. Specifically, coaches can use the %HRmax to quantify internal loads (%VO(2)max) and subsequently implement continuous endurance training at appropriate intensities. Furthermore, it seems that RPE is more useful as a measure of internal load during noncontinuous (e.g., intermittent and sprint) exercises but not to estimate %VO(2)max during continuous aerobic exercise (R = 59%).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".