Intensity selection and regulation using the OMNI scale of perceived exertion during intermittent exercise
Bibliographic record
Abstract
The purpose of this investigation was to determine if subjects can self-regulate exercise intensity during intermittent exercise by using ratings of perceived exertion. Thirty-one subjects completed an estimation trial maximal treadmill graded exercise test (GXT). Using the oxygen uptake and ratings of perceived exertion (RPE) from the GXT, target RPEs that corresponded to 50% and 70% of oxygen uptake reserve were determined. During the subsequent 20 min production trial, subjects titrated treadmill speed and grade to elicit the target RPEs that were presented in 2 counterbalanced orders (counterbalance order I (70%-50% of oxygen uptake reserve) or counterbalance order II (50%-70% of oxygen uptake reserve)). Heart rate (HR) and oxygen uptake were higher in the production trial compared with the estimation trial for counterbalance order I (p < 0.001) at an RPE that corresponded to 50% of oxygen uptake reserve. There was no difference in HR and oxygen uptake between the estimation and production trial for counterbalance order II (p < 0.05). HR was higher in the production trial compared with estimation trial for counterbalance order I (p < 0.05) at an RPE that corresponded to 70% of oxygen uptake reserve. There was no difference in HR between the estimation and production trials for counterbalance order II (p < 0.05). At an RPE that corresponded to 70% of oxygen uptake reserve, there was no difference in the oxygen uptake between the estimation and production trials (p < 0.05). A difference in HR (p < 0.05) and oxygen uptake (p < 0.05) between the 2 prescribed production trial intensities was indicated. The subjects were able to utilize RPE to self-regulate intensity during 20 min of exercise at varying intensity when beginning with the target RPE that corresponded to 50% of oxygen uptake reserve.
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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 | 0.003 |
| 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".