Modification of the Wingate Anaerobic Power Test for Rowing: Optimization of the Resistance Setting
Bibliographic record
Abstract
The purpose of the study was to determine the resistance factor that would elicit the highest peak 5 s and mean 30 s power output (PO) during a maximal 30 s anaerobic power test on a rowing ergometer. Thirty-one rowers (17 male and 14 female) were recruited based on the light-weight (LW) (6 male; age 23 +/- 6 yrs and 6 female; age 19 +/- 2 yrs) and heavy-weight (HW) (11 male; age 24 +/- 4 yrs and 8 female; age 27 +/- 8 yrs) rowing categories. Each group completed 5 randomized series of maximal 30 s sprints equivalent to the following forces: 58.9, 63.8, 68.7, 73.7 and 78.6 N for LW males; 83.5, 88.4, 93.4, 98.2 and 103.1 N for HW males; 29.4, 34.3, 39.2, 44.1 and 49.1 N for LW females; and 44.1, 49.1, 54.0, 58.6 and 63.8 N for HW females. The tests were performed on a Gjessing rowing ergometer modified to accommodate greater resistance settings and computer linked to obtain the necessary data. The peak 5 s and mean 30 s PO (W) were determined for each test. A relative load factor (RLF) for determining the amount of resistance to be applied was calculated based on body mass (BM). The RLF settings that elicited the highest peak 5 s PO were 0.109 and 0.102 kg. kg (-1) BM for LW and HW male rowers and 0.111 kg. kg (-1) BM and 0.076 kg. kg (-1) BM for LW and HW female rowers, respectively. The RLF settings for eliciting the highest mean 30 s PO were 0.102 and 0.095 kg. kg (-1) BM for LW and HW male rowers and 0.103 kg. kg (-1) BM and 0.068 kg. kg (-1) BM for LW and HW female rowers, respectively. A 30 second anaerobic test was also performed on a Concept II rowing machine for comparison and it was found to elicit a significantly lower peak 5 s but not 30 s PO in both male and female rowers. Our findings provide RLFs for assessing anaerobic power using a 30 s test in male and female rowers. As well, peak 5 s but not mean 30 s PO is underestimated using the Concept II rowing machine.
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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".