Pacing of an Untrained 17-Year-Old Teenager in a Marathon Attempt
Bibliographic record
Abstract
International Journal of Exercise Science 11(6): 856-866, 2018. Although there has been increased scientific interest for physiological responses to endurance running and pacing, limited information exists for adolescents participating in endurance events. We are reporting the case of an untrained 17-year-old female teenager (body mass 50.6 kg, height 167 cm and body mass index 18.1 kg/m2) who intended to run a marathon within 6 hours without preparation. The young woman missed her goal by just 2 km. When the average running speed per hour was analysed, there was a major effect of race hour on running speed (p = 0.013, h2 = 0.320), where the running speed in the fifth hour (6.3 ± 0.2 km/h) was lower than in the second hour (6.9 ± 0.1 km/h). Despite a progressive decrease in running speed, she was still able to put on a final spurt, indicated by a 4th degree non-linear regression (R2=0.55). Creatine-kinase reached the initial value again after 5 days and the fall of hemoglobin and hematocrit indicated expansion of plasma volume. Running a marathon as a teenager did not impair physical health, especially when a self-selected pace was adopted. Laboratory parameters during running showed similar changes as have been reported for teenagers and adults after running a marathon. Increased values returned to base line within a few days. In summary, a female teenager at the age of 17 years without specific running preparation is able to achieve nearly a marathon distance during 6 hours of continuous running without harmful effects on health.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".