Dietary Microperiodization in Elite Female and Male Runners and Race Walkers During a Block of High Intensity Precompetition Training
Bibliographic record
Abstract
We investigated one week of dietary microperiodization in elite female (n = 23) and male (n = 15) runners and race-walkers by examining the frequency of training sessions and recovery periods conducted with recommended carbohydrate (CHO) and protein availability. Food and training diaries were recorded in relation to HARD (intense or >90min sessions; KEY) versus RECOVERY days (other-than KEY sessions; EASY). The targets for amount and timing of CHO and protein around KEY sessions were based on current nutrition recommendations. Relative daily energy and CHO intake was significantly (p < .05) higher in males (224 ± 26 kJ/kg/d, 7.3 ± 1.4 g/kg/d CHO) than females (204 ± 29 kJ/kg/d, 6.2 ± 1.1 g/kg/d CHO) on HARD days. However, when adjusted for training volume (km), there was no sex-based difference in CHO intake daily (HARD: 0.42 ± 0.14 vs 0.39 ± 0.15 g/kg/km). Females appeared to periodize energy and protein intake with greater intakes on HARD training days (204 ± 29 vs 187 ± 35 kJ/kg/d, p = .004; 2.0 ± 0.3 vs 1.9 ± 0.3 g/kg/d protein, p = .013), while males did not periodize intakes. Females showed a pattern of periodization of postexercise CHO for KEY vs EASY (0.9 ± 0.4 vs 0.5 ± 0.3 g/kg; p < .05) while males had higher intakes but only modest periodization (1.3 ± 0.9 vs 1.0 ± 0.4; p = .32). There was only modest evidence from female athletes of systematic microperiodization of eating patterns to meet contemporary sports nutrition guidelines. While this pattern of periodization was absent in males, in general they consumed more energy and CHO daily and around training sessions compared with females. Elite endurance athletes do not seem to systematically follow the most recent sports nutrition guidelines of periodized nutrition.
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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".