Age of peak performance in elite male and female Ironman triathletes competing in Ironman Switzerland, a qualifier for the Ironman world championship, Ironman Hawaii, from 1995 to 2011
Bibliographic record
Abstract
BACKGROUND: The age of peak performance in elite endurance athletes has been investigated for elite marathoners, but not for elite Ironman triathletes. The aim of this study was to analyze the age of peak performance in swimming (3.8 km), cycling (180 km), running (42 km), and overall race time for elite female and male Ironman triathletes competing in Ironman Switzerland, a qualifier for the Ironman world championship, known as the Ironman Hawaii. METHODS: The age of the annual top ten overall swimmers, cyclists, runners, and annual overall finishers for both male and female elite triathletes and their corresponding split and overall race times at the Ironman Switzerland were analyzed between 1995 and 2011. RESULTS: The mean age of the elite Ironman triathletes was 33 ± 3 years for men and 34 ± 4 years for women. For women, the age of peak performance was not significantly different between the three disciplines (P > 0.05), while for men, the best swimmers (29 ± 3 years) were significantly (P < 0.05) younger than the best runners (35 ± 5 years). During the study period, the age of peak performance remained unchanged for men at 31 ± 3 years (P > 0.05), but increased for women from 30 ± 4 years in 1995 to 36 ± 5 years in 2011 (P < 0.01). CONCLUSION: Although both women and men improved their overall race times during the 1995-2011 period, the age of peak performance was similar between women and men in the three disciplines and in overall race time. Future studies need to examine the change in age of peak performance across years in the Ironman Hawaii world championship event.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".