Energy Balance during an Ironman Triathlon in Male and Female Triathletes
Bibliographic record
Abstract
Energy balance of 10 male and 8 female triathletes participating in an Ironman event (3.8-km swim, 180-km cycle, 42.2-km run) was investigated. Energy intake (EI) was monitored at 7 designated points by dietary recall of food and fluid consumption. Energy expenditure (EE) during cycling and running was calculated using heart rate-VO, regression equations and during swimming by the multiple regression equation: Y = 3.65v+ 0.02W- 2.545 where Yis VO,in L x min(-1), v is the velocity in m s(-1), Wis the body weight in kilograms. Total EE (10,036 +/- 931 and 8,570 +/- 1,014 kcal) was significantly greater than total EI (3,940 +/- 868 and 3,115 +/- 914 kcal, p <.001) for males and females, respectively, although energy balance was not different between genders. Finishing time was inversely related to carbohydrate (CHO) intake (g x kg(-1) x h(-1)) during the marathon run for males (r = -.75,p <.05), and not females, suggesting that increasing CHO ingestion during the run may have been a useful strategy for improving Ironman performance in male triathletes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 0.001 |
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".