Evaluation of the “Step-Ramp-Step” Protocol: Accurate Aerobic Exercise Prescription with Different Steps and Ramp Slopes
Bibliographic record
Abstract
PURPOSE: To assess whether: i) a lower amplitude constant-load MOD is appropriate to determine the mean response time (MRT); ii) the method accurately corrects the dissociation in the V̇O 2 -PO relationship during ramp compared with constant-load exercise when using different ramp slopes. METHODS: Eighteen participants (7 females) performed three SRS tests including: i) step-transitions into MOD from 20 to 50 W (MOD 50 ) and 80 W (MOD 80 ); and ii) slopes of 15, 30, and 45 W·min -1 . The V̇O 2 and PO at the gas exchange threshold (GET) and the corrected respiratory compensation point (RCP CORR ) were determined. Two to three 30-min constant-load trials evaluated the V̇O 2 and PO at the maximal metabolic steady state (MMSS). RESULTS: There were no differences in V̇O 2 at GET (1.97 ± 0.36, 1.99 ± 0.36, 1.95 ± 0.30 L·min -1 ), and RCP (2.81 ± 0.57, 2.86 ± 0.59, 2.84 ± 0.59) between 15, 30, and 45 W·min -1 ramps, respectively ( P > 0.05). The MRT in seconds was not affected by the amplitude of the MOD or the slope of the ramp (range 19 ± 10 s to 23 ± 20 s; P > 0.05). The mean PO at GET was not significantly affected by the amplitude of the MOD or the slope of the ramp (range 130 ± 30 W to 137 ± 30 W; P > 0.05). The PO at RCP CORR was similar for all conditions ((range 186 ± 43 W to 193 ± 47 W; P > 0.05). CONCLUSIONS: The SRS protocol accounts for the V̇O 2 MRT when using smaller amplitude steps, and for the V̇O 2 slow component when using different ramp slopes, allowing for accurate partitioning of the exercise intensity domains in a single test.
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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 | 0.000 | 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) | 0.002 | 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".