Metabolic parameters for ramp versus step incremental cycle ergometer tests
Bibliographic record
Abstract
The purpose of this study was to examine mean differences and the patterns of responses for oxygen uptake ([Formula: see text]O(2)), heart rate (HR), and rating of perceived exertion (RPE) for ramp (15 W·min(-1)) versus step (30 W increments every 2 min) incremental cycle ergometer tests. Fourteen subjects (age and body mass of 23.2 ± 3.1 (mean ± SD ) years and 71.1 ± 10.1 kg, respectively) visited the laboratory on separate occasions. Two-way repeated measures ANOVAs with appropriate follow-up procedures, as well as paired t tests, were used to analyze the data. In addition, polynomial regression analyses were used to determine the patterns of responses for each dependent variable for the ramp and step tests. The ramp protocol resulted in lower mean [Formula: see text]O(2) and HR values at the common power outputs than the step protocol with no differences in RPE. The increased amount of work performed during the step (total work = 75.83 kJ) versus ramp (total work = 65.60 kJ) tests at the common power outputs may have contributed to the greater [Formula: see text]O(2) and HR values. The polynomial regression analyses showed that most subjects had the same patterns of responses for the ramp and step incremental tests for HR (86%) and RPE (93%) but different patterns for [Formula: see text]O(2) (71%). The findings from the present study suggested that the protocol selection for an incremental cycle ergometer test can affect the mean values for [Formula: see text]O(2) and HR, as well as the [Formula: see text]O(2) - power output relationship.
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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) | 0.003 | 0.001 |
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".