Predictor variables for half marathon race time in recreational female runners
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: The relationship between skin-fold thickness and running performance has been investigated from 100 m to the marathon distance, except the half marathon distance. OBJECTIVE: To investigate whether anthropometry characteristics or training practices were related to race time in 42 recreational female half marathoners to determine the predictor variables of half-marathon race time and to inform future novice female half marathoners. METHODS: Observational field study at the 'Half Marathon Basel' in Switzerland. RESULTS: In the bivariate analysis, body mass (r = 0.60), body mass index (r = 0.48), body fat (r = 0.56), skin-fold at pectoral (r = 0.61), mid-axilla (r = 0.69), triceps (r = 0.49), subscapular (r = 0.61), abdominal (r = 0.59), suprailiac (r = 0.55) medial calf (r = 0.53) site, and speed of the training sessions (r = -0.68) correlated to race time. Mid-axilla skin-fold (p = 0.04) and speed of the training sessions (p = 0.0001) remained significant after multi-variate analysis. Race time in a half marathon might be predicted by the following equation (r² = 0.71): Race time (min) = 166.7 + 1.7x (mid-axilla skin-fold, mm) - 6.4x (speed in training, km/h). Running speed during training was related to skinfold thickness at mid-axilla (r = -0.31), subscapular (r = -0.38), abdominal (r = -0.44), suprailiacal (r = -0.41), the sum of eight skin-folds (r = -0.36) and percent body fat (r = -0.31). CONCLUSION: Anthropometric and training variables were related to half-marathon race time in recreational female runners. Skin-fold thicknesses at various upper body locations were related to training intensity. High running speed in training appears to be important for fast half-marathon race times and may reduce upper body skin-fold thicknesses in recreational female half marathoners.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it