Biomechanical analysis to determine the external power output on an immersible ergocycle
Bibliographic record
Abstract
The external power output (Pext) is unknown during chest-level immersion exercise on water immersible ergocycles (IE). This knowledge will allow the practitioner to prescribe accurately exercise on an IE to the same workload on dryland ergocycle (DE). To develop a mathematical model to calculate Pext during chest-level immersion exercise on IE at different pedalling rates (rpm) taking into account the water external force exerted on the legs and pedalling mechanism. Thirty healthy participants (age: 33 ± 10 years) performed a maximal incremental exercise test on IE (chest-level immersion) and on a DE. Pedalling rate was increased by 10 rpm every minute beginning at 40 till 120 rpm. Pext was calculated by applying the general fluid equation [Formula: see text] on all elements exposed to water external force exertions (legs and pedalling system). Regression analysis yielded the following equations to determine (1) IE Pext (W) based on pedalling rate (rpm): Pext (W) = 0.0004 (rpm)(2.993) (r(2) = 0.99, SEE = 7.6 W, p < 0.0001) and (2) when DE Pext (W) is known, IE pedalling rate (rpm) = 13.91 × DE Pext (W)(0.329) (r(2) = 0.99, SEE = 1.5 W, p < 0.0001). This study provides a mathematical model based on the general fluid equation to calculate IE Pext during chest-level immersion exercise using pedalling rate (rpm), IE pedalling system physical characteristics and lower limb size. This model can be used to determine Pext for any IE type for exercise training prescription.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".