METABOLIC DEMAND OF LEG DRIVE IN OUTRIGGER CANOE PADDLERS
Bibliographic record
Abstract
Leg drive is encouraged in paddling to increase power per stroke. When involving additional muscle mass during exercise, it can be expected that the metabolic demand would also increase. PURPOSE: to investigate the metabolic demand of paddling with and without leg drive compared to whole-body exercise in trained and untrained individuals. METHODS: Treadmill (TM) and paddling ergometer with leg drive (PEL) and with no leg drive (PENL) incremental testing to fatigue was recorded in 22 healthy male subjects. Eleven experienced outrigger canoeists (P) (age = 35.64 ± 5.66 yrs, ht = 179.16 ± 3.81 cm, wt = 84.39 ± 9.23 kg) and eleven matched controls (C) (age = 36.45 ± 5.66 yrs, ht = 178.85 ± 4.07 cm, wt = 83.95 ± 8.32 kg) participated. Metabolic variables were monitored using a portable metabolic system. RESULTS: Oxygen consumption of the paddlers was significantly increased with the addition of leg drive during maximal exercise on the paddling ergometer (PEL = 3.88 ± 0.53, PENL = 3.23 ± 0.47 L/min) (p < 0.01). Paddlers also attained a higher percentage (14.58% higher than controls) of treadmill VO2max when using leg drive. Furthermore, the paddling group was able to reach higher percentages of treadmill VO2max during paddling tests both with legs (P = 85.05 ± 7.82 vs. C = 67.52 ± 4.58) and without legs (P = 70.47 ± 5.47 vs. C = 61.79 ± 4.16) when compared to the control group (p < 0.01). Maximal minute ventilation (VE) was not significantly different between tests for the paddlers (TM = 149.97 ± 13.90, PEL = 151.91 ± 17.30, PENL = 141.41 ± 20.60 L/min). However, controls attained a significantly higher VEmax during TM (131.43 ± 16.99 L/min) when compared to PEL (110.18 ± 15.20 L/min) and PENL (104.22 ± 14.08 L/min) (p < 0.01). With leg drive (PEL) paddlers were able to achieve similar maximal heart rate (HR) values to the TM, while HRmax for PENL was significantly lower (TM = 183.36 ± 11.38, PEL = 175.73 ± 9.39, PENL = 171.27 ± 11.46 bpm) (p < 0.01). Treadmill HRmax (187.64 ± 12.68 bpm) in controls was significantly higher than both PEL (172.36 ± 13.34 bpm and PENL (73.82 ± 11.12 bpm) (p < 0.01). CONCLUSION: These results suggest that leg drive does significantly contribute to the metabolic demand of paddling in outrigger canoeists. Supported by the BC Sports Medicine Research Foundation
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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 | 0.000 |
| 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) | 0.001 | 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".