Training Effects on Nutrient Intake in Male Collegiate Cross Country Runners
Bibliographic record
Abstract
2373 Physical activity and athletic performance are enhanced by optimal nutrition. There have been few studies published investigating the dietary practices of college-age male cross-country runners. PURPOSE: To assess the nutritional adequacy of collegiate cross-country runners at three phases during their competitive season. METHODS: Three-day diet records of nine male collegiate cross-country runners were collected at three phases during a season: early season, pre-taper, and during the taper. Assessment of the nutritional adequacy of their diets was based on the Joint Position Statement published by the American College of Sports Medicine, the American Dietetic Association, and the Dietitians of Canada. RESULTS: The mean carbohydrate intake (7.9g/kg) was within the recommended range, while fat intake (33% of total energy intake) and protein intake (2.0g/kg) were consistently above the recommendations. The mean intake for all micronutrients analyzed met the Recommended Dietary Allowances (RDA) except for magnesium (61%) and vitamin E (67%). There was a tendency for all macro- and micro-nutrients to decrease from early season to pretaper and then increase during the tapering phase. Magnesium and vitamin B6 intake decreased significantly from early season to pre-taper by 29% and 34%, respectively. CONCLUSIONS: Although the mean intake for most micronutrients was close to 100% of the RDAs, a significant proportion of individual runners were not meeting the RDA. Collegiate cross-country runners should consume nutrient dense diets to insure adequate nutrient intake throughout the cross-country season.
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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 | 0.001 |
| 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 | 0.000 |
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 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".