Rapid body mass loss affects erythropoiesis and hemolysis but does not impair aerobic performance in combat athletes
Bibliographic record
Abstract
Rapid body mass loss (RBML) before competition was found to decrease hemoglobin mass (Hbmass ) in elite boxers. This study aimed to investigate the underlying mechanisms of this observation. Fourteen well-trained combat athletes who reduced body mass before competitions (weight loss group, WLG) and 14 combat athletes who did not practice RBML (control group, CON) were tested during an ordinary training period (t-1), 1-2 days before an official competition (after 5-7 days RBML in WLG, t-2), and after a post-competition period (t-3). In WLG, body mass (-5.5%, range: 2.9-6.8 kg) and Hbmass (-4.1%) were significantly (P < 0.001) reduced after RBML and were still decreased by 1.6% (P < 0.05) and 2.6% (P < 0.001) at t-3 compared with t-1. After RBML, erythropoietin, reticulocytes, haptoglobin, triiodothyronine (FT3 ), and free androgen index (FAI) were decreased compared with t-1 and t-3. An increase occurred in ferritin and bilirubin. Peak treadmill-running performance and VO2peak did not change significantly, but performance at 4-mmol lactate threshold was higher after RBML (P < 0.05). In CON, no significant changes were found in any parameter. Apparently, the significant decrease in Hbmass after RBML in combat athletes was caused by impaired erythropoiesis and increased hemolysis without significant impact on aerobic performance capacity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".