Pacing pattern and performance during the 2008 Olympic rowing regatta
Bibliographic record
Abstract
Abstract Data from the 2008 Olympic rowing regatta were analysed to determine the time distribution during races and to assess whether pacing patterns differ between heats and the corresponding finals. Absolute and relative sector times for all of the four 500 m race quarters were analysed, for all boats in all heavyweight heats and final races (n=72 boats for men, n=60 boats for women). Irrespective of race type, boat rank or boat type, analyses of variance with repeated measures revealed that absolute times in the second and/or third race quarter(s) were significantly (both sexes: P<0.001) longer than those either in the first or final quarter, resulting in a parabolic‐shaped profile. Compared with the heats, the pacing pattern adopted during the finals was significantly different (females: P<0.013; males: P<0.001); that is, relatively slower in the first and second race quarter but relatively faster in the last quarter. The parabolic‐shaped race profile indicates an anticipatory control of speed and energy distribution over the course of the 2000‐m race. The observed changes in pacing pattern suggest that during the finals a more conservative starting pace is used, which could be physiologically advantageous, because some energy is withheld for the final spurt.
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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".