Variation of Salivary IgA During Weight Loss Period Before a Competition Among University Judo Players
Bibliographic record
Abstract
BACKGROUND: This study aims to investigate the health condition of university judo athletes during a period of weight loss before a competition, using secretory immunoglobulin A (SIgA) in saliva. METHODS: The subjects were 30 university judo athletes, who were divided into three groups: control group (n = 10), under 5% weight loss group (n = 10), and over 5% weight loss group (n = 10). The items evaluated were body weight measurements, salivary SIgA level and its secretion rates, incidences of symptoms of upper respiratory tract infections, and mental state. RESULTS: The over 5% body weight loss group had significantly lower SIgA secretion rates on the first day and third day before the real competition compared to those of the control group. Furthermore, the over 5% body weight loss group had an increased number of symptoms of upper respiratory tract infections. Alterations in mental statuses were also seen, such as decreased vitality and increased fatigue on the day before the competition in the over 5% weight loss group. CONCLUSIONS: This study shows that over 5% body weight loss in judo athletes induces a decrease in the salivary SIgA secretion rate and causes health condition of the body and the mind to deteriorate.
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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".