IRONMAN® Hawaii is the fastest race course for age group triathletes (Preprint)
Bibliographic record
Abstract
BACKGROUND The IRONMAN® triathlon is a popular multi-sport, where age group athletes often strive to qualify for the IRONMAN® World Championship in Hawaii. The aim of the present study was to investigate the location of the fastest IRONMAN® racecourses for age group triathletes. This knowledge will help IRONMAN® age group triathletes find the best racecourse, considering their strengths and weaknesses, to qualify. OBJECTIVE To determine the fastest IRONMAN® racecourse for age group triathletes using the machine learning XG Boost algorithm. METHODS We collected and analyzed 677,702 age group finishers' records from 228 countries participating in the IRONMAN® competitions held between 2002 and 2022 across 67 event locations. A predictive model was built with the race finish time as the predicted variable and the triathlete’s gender, age group, country of origin, and event location as predictors. The model was trained with 75% of the available data and was validated against the remaining 25%. Several model interpretability tools were used to explore how each predictor contributed to the model's predictive power, from which we intended to infer whether one or more predictors were more important than the others. RESULTS The XG Boost Regressor model analysis indicated that the IRONMAN® Hawaii course was the fastest racecourse and that male athletes aged 35 years and younger were the fastest. Most of the finishers were competing in IRONMAN® triathlons held in the USA, such as IRONMAN® Wisconsin, Florida, Lake Placid, Arizona, and Hawaii, where the IRONMAN® World Championship takes place. Still, the fastest average times were achieved in IRONMAN® Hawaii, Austria, Copenhagen, Brazil Florianopolis, and Barcelona. Most of the successful IRONMAN® finishers originated from the United States of America, followed by athletes from the United Kingdom, Canada, Australia, Germany, and France. The best mean IRONMAN® race times were achieved by athletes from Austria, Germany, Belgium, Switzerland, Finland, and Denmark. CONCLUSIONS Age group athletes who have better placements in faster events and intend to qualify for IRONMAN® Hawaii may participate in IRONMAN® Austria, Copenhagen, Brazil Florianopolis, and Barcelona in order to achieve a fast race time to qualify for the IRONMAN® World Championship in Hawaii. CLINICALTRIAL -
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.062 | 0.013 |
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".