<Originals>The Effect of the Cycle Phase on Run Performance in an Ultraendurance Triathlon
Bibliographic record
Abstract
LAURSEN, P.B., THODES, E.C., LANGILL, R.H., McKENZIE, D.C. and TAUNTON, J.e., The Effect of the Cycle Phase on Run Performance in an Ultraendurance Triatholon. Adv. Exerc. Sports Physiol., Vol.7, No.3 pp.81-86, 2001. The purpose of this study was to investigate the effects of the cycle phase on the subsequent run performance in an ultraendurance triathlon. In addition, a secondary purpose was to examine the predicitive ability of VO2[?] and T[?] on an actual triathlon run performance. At first, ten highly trained male ultraendurance triathleters (x±SEM: age=36.5±1.5 yrs: body fat=12.2±1.2%) performed an incremental treadmill test (Tr1) to measure VO2[?] and T[?]. Secondly, a 5-h bike time trial (Bissp) was performed. and was immediately follwed by a second incremental treadmill test (Tr2). VO2[?] and T[?] were not significantly different between trials (x±SEM: VO2[?] -46.5±0.16 vs. 4.31±0.14 L-min VO2 at T[?]=3.35±0.11 vs. 3.15±0.11 L-min p>o.o5; Trl ws Tr2 respectvely). Furthermore, the T[?] estimation from Tr2 was not at a significantly reduced speed (x=SEM: Tr1 T[?]=8.8±0.2 mph. Tr2 T[?] -8.3±0.2 mph: p>0.05) and neither of these significantly correlated (r -0.473 to r -0.366: p>0.05 Tr1 to Tr2 respectively) with the actual Ironman Canada triathlon run pace (5.9±0.3 mph). Findings differ somewhat from recently reported Olympoic distance triatholon research. Prediction of run performance in an lrinman triathlon is difficult and likely the interaction of many confounding variables (such as fuel utilization and dehydration) not present to the same degree at the shorter distance.
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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 | 0.001 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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".