Maximal peak power from a reliable and race-specific protocol is associated with both 2000 m and 1500 m elite rowing performance
Bibliographic record
Abstract
Maximal peak power (MPP) is strongly associated with 2000 m rowing performance and is likely to become a critical predictor of success with the shift to 1500 m racing at the 2028 Olympic Games. However, no consensus exists on a standardized protocol for assessing MPP in rowing. This study examined the reliability of a 10-stroke ergometer-based MPP test in elite under-23 rowers, assessing its association with time-trial performance. Thirty-three athletes (10 females) completed 10 MPP tests across five sessions. The protocol included five lead-in strokes followed by five maximal strokes at 40 strokes per minute. As greatest MPP values were consistently obtained during the first test, the second test of each session was excluded from analyses. Mean (±SD) bias between the three experimental sessions was 1.0 (±0.4)% for males and 0.9 (±0.7)% for females. The test demonstrated near perfect between-session reliability, with intraclass correlation coefficients ranging from 0.92 to 0.99. A near perfect relationship was found between MPP and 2000 m (r = 0.93) and 1500 m (r = 0.94) ergometer performance. This protocol provides a reliable, valid, and practical tool for assessing true MPP improvements and profiling athletes within a stroke rate that mirrors contemporary on-water racing demands.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| 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 | 0.001 | 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".