Protein and Leucine Requirements for Maximal Muscular Development and Athletic Performance Are Achieved with Completely Plant-Based Diets Modeled to Meet Energy Needs in Adult Male Rugby Players
Bibliographic record
Abstract
Rugby athletes consume large amounts of animal protein in accordance with conventional dietary guidance to increase muscle mass and strength. This misaligns with national dietary guidelines, which suggest limiting meat consumption for chronic disease prevention. The ability of completely plant-based diets to satisfy the nutritional needs of rugby players has not been explored. This study scaled nutrient data from a large population consuming completely plant-based diets with limited supplemental protein to meet the calorie requirements of adult male rugby athletes to assess whether protein and leucine recommendations for muscular development and athletic performance would be achieved. Calorie requirements were estimated from research that employed the doubly labeled water method, and dietary data from the Adventist Health Study-2 were scaled to this level. The modeled protein level was 1.68 g/kg/day, which meets recommendations for maximal gains in muscle mass, strength, and athletic performance. The modeled leucine level was 2.9 g/meal for four daily meals, which exceeds the threshold proposed to maximally stimulate muscle protein synthesis in young men. These results indicate that consuming large portions of completely plant-based meals can satisfy protein and leucine requirements for maximal muscular development and athletic performance in adult male rugby athletes while aligning with public health recommendations.
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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".