Evaluation of the Monark Wingate Ergometer by Direct Measurement of Resistance and Velocity
Bibliographic record
Abstract
The purpose of this study was to assess the accuracy of the new basket-loaded Wingate ergometer introduced by Monark (Model 834E). Velocity was measured directly from the pedal switch while tension was measured with transducers on each end of the brake lacing. Moment of inertia of the flywheel was determined and accounted for in the calculation of power. Constant load tests (39.24 to 98.1 N), were done at pedaling speeds from 80 to 140 r x min(-1) (flywheel angular velocity = 30-50 rad x s(-1)). The load transmitted to the lacing at the front and back of the flywheel was 95.5 +/- 0.8% (mean +/- SEM) and 6.71 +/- 0.8%, respectively, of the load in the basket. Thus, the resultant tension (front minus back) was on average 88.8 +/- 0.57% of the applied load. The velocity recorded by the Monark Wingate Ergometer computer program (MWECP) was the same (100.4 +/- 1.56%) as that determined from the pedal switch directly. Five male mountain bikers performed a 30-s all-out test. Peak power calculated by MWECP (1181 +/- 55W) was always higher (p < .01) than that calculated from direct measures of tension and velocity (1102 +/- 66W), when not taking into account the moment of inertia. These experiments suggest that the basket-loaded Monark Wingate ergometer does not provide a correct calculation of power because of incomplete load transmission to the flywheel.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".