Time-Motion Analysis, Heart Rate, and Physiological Characteristics of International Canoe Polo Athletes
Bibliographic record
Abstract
To evaluate the time international canoe polo players spend performing various game activities, measure heart rate (HR) responses during games, and describe the physiological profile of elite players. Eight national canoe polo players were videotaped and wore HR monitors during 3 games at a World Championship and underwent fitness testing. The mean age, height, and weight were 25 ± 1 years, 1.82 ± 0.04 m, and 81.9 ± 10.9 kg, respectively. Time-motion analysis of 3 games indicated that the players spent 29 ± 3% of the game slow and moderate forward paddling, 28 ± 5% contesting, 27 ± 5% resting and gliding, 7 ± 1% turning, 5 ± 1% backward paddling, 2 ± 1% sprinting, and 2 ± 1% dribbling. Sixty-nine (±20)% of the game time was played at an HR intensity above the HR that corresponded to the ventilatory threshold (VT) that was determined during the peak V[Combining Dot Above]O2 test. Peak oxygen uptake and VT were 3.3 ± 0.3 and 2.2 ± 0.3 L·min, respectively, on a modified Monark arm crank ergometer. Arm crank peak 5-second anaerobic power was 379 W. The majority of the time spent during international canoe polo games involved slow-to-moderate forward paddling, contesting for the ball, and resting and gliding. Canoe polo games are played at a high intensity indicated by the HR responses, and the physiological characteristics suggest that these athletes had high levels of upper body aerobic and anaerobic fitness levels.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".