Effects of two entrainment patterns on performance of female novice rowers
Bibliographic record
Abstract
Objectives: Rowers who entrain breathing frequency to stroke rate do so in either a 1:1 or 2:1 pattern. The purpose of this study was to investigate the performance and physiological difference that occurs between the practice of these two patterns of breathing. Methods: Fifteen novice female rowers (age =19.7 ± 1.6 yr.; body mass = 70.9 ±6.3 kg; height = 174.4 ±4.4 cm) were randomly assigned to complete a 2000 meter rowing ergometer test alternatively using each breathing pattern one week apart. Expired gases and breathing frequencies were measured using a Medical Graphics CPX‐D metabolic system. Heart rate (fc) was recorded using direct lead ECG. Stroke rate was obtained from the Concept II Ergometer. Results: Repeated measures MANOVA determined that when the breathing frequency was 2 breaths per stroke (2:1 versus 1:1), the time to complete the test was significantly shorter (490 ± 24.8 vs. 514 ± 11.3 s, p ≤ 0.05) and power output was greater (203.4 ± 21.5 vs. 184.5 ± 20.4 W, p ≤ 0.05). Oxygen uptake during each test did not differ significantly (2:1 = 2.7 ± 0.2; 1:1 = 2.5 ± 0.4 L/min, p > 0.05) despite an increased heart rate during the 2:1 trial (186.5 ± 8.9 vs. 175.7 ± 17.0 bpm, p = ≤ 0.05). The end tidal carbon dioxide tension (PETCO2) and tidal volume values were significantly lower during the 2:1 vs. the 1:1 condition (35.8±3.3vs. 45.1±3.4mmHg, p ≤ 0.05) and (2.1±0.3vs. 2.6 ± 0.3 L, p ≤ 0.05) respectively. Conclusion: Entrainment at 2 breaths per stroke results in a significant improvement in performance during a standard 2000 m rowing ergometer test compared to a 1:1 pattern of breathing. Entrainment of one breath per stroke leads to carbon dioxide retention, which may result in respiratory acidosis and a negative impact on performance.
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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 | 0.000 | 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".