Dietary Macronutrient and Micronutrient Intake over a 7-Day Period in Female Varsity Ice Hockey Players
Bibliographic record
Abstract
This study examined the energy, macronutrient, and micronutrient intakes of female ice hockey players over a 7-d period including game, practice, and rest days. Twenty-three female varsity players (19.0 ± 1.1 yr, 167.1 ± 6.5 cm, 67.0 ± 8.0 kg) volunteered for the study. Average total daily energy expenditure (TDEE) was estimated over the 7-day period. Average 7-day energy intake (EI) and TDEE were 2354 ± 353 and 2304 ± 204 kcal. The majority (n = 19) of athletes had an EI ≥ 90% of their estimated TDEE. Macronutrient intake was 52% carbohydrate (CHO), 32% fat, and 16% protein of total EI, although CHO intake was slightly below recommendations (5 g/kg BM/d) on game and practice (4.8 ± 1.4 and 4.5 g/kg BM/d) days. Game day EI was greater than practice and rest days. Recommended micronutrient intakes were not met by most athletes for iron, calcium, vitamin D, and potassium, and intakes were similar between game, practice, and rest days. In summary, the average EI for female varsity ice hockey players appeared adequate to meet their energy needs over a weekly cycle of game, practice, and rest days. However, these female athletes would benefit from increasing CHO intake on game and practice days and selecting foods that are rich in vitamins and minerals.
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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 | 0.000 | 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) | 0.001 | 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".