Sex differences and indications of metabolic compensation in within-day energy balance in elite Division 1 swimmers
Bibliographic record
Abstract
To determine whether mismatched energy intake and expenditure across the day and associated sex differences may be related with metabolic compensation and/or negative health outcomes, we assessed total-day and hourly energy balance (TDEB and EB), total-day and hourly energy intake (TDEI and EI), total-day and hourly energy expenditure (TDEE and EE) and within-day energy balance (WDEB) in elite male and female swimmers ( n = 25; 18–22 years). Total triiodothyronine (TT3), resting metabolic rate (RMR), and the ratio of actual-to-predicted RMR were determined. Males exhibited higher TDEB (+758 ± 702 kcal vs +52 ± 505 kcal, t-test; p = 0.007) than females. Males exhibited a more positive hourly EB, driven by greater hourly EI at 11:00, 13:00, 16:00, and 19:00 h (ANOVA, p < 0.05), while EE did not differ. TT3 was negatively correlated with consecutive hours of negative EB ( R = −0.604, p = 0.049) and positively correlated to hours in EB ( R = 0.740, p = 0.009) in those exhibiting metabolic suppression ( n = 12). In individuals in TDEB ( n = 21), “backloaders” (consumption of ≥50% daily kcals at or after 1700 h) had lower TT3 (79.3 ng/dL vs 92.9 ng/dL, p = 0.009) than “nonbackloaders” ( n = 12). WDEB analyses indicate a greater risk of energy deficiency in females and may capture indices of metabolic compensation not evident with EB analyses alone.
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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 | 0.000 | 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) | 0.002 | 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".