Effect of Protein, Dairy Components and Energy Balance in Optimizing Body Composition
Bibliographic record
Abstract
Weight loss is achieved through the consumption of a hypoenergetic diet and/or increased energy expenditure through exercise. While weight loss is associated with numerous benefits, the pattern of weight loss in terms of body composition changes is not always studied. In our view, the optimum pattern of weight loss is one in which fat mass is lost and lean mass is preserved. The preservation of lean mass has important consequences due to the role of this tissue in contributing to basal metabolic rate, controlling glycemia, and contributing to lipid oxidation. We also propose that a preservation of lean mass would have important consequences in resisting weight regain after loss. We review dietary practices, including reduced consumption of dietary carbohydrate, consuming higher than recommended dietary protein, with an emphasis on dairy sources, as well as dietary calcium, to accelerate the loss of fat mass during dieting and preserve lean mass. Available evidence suggests that each practice has a highly plausible mechanistic and growing clinical rationale in terms of efficacy in promoting fat mass loss and lean mass retention during a hypoenergetic diet.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".