The Relationship Between Relative Age and Tournament Success for 11-Year-Old Male Wrestlers in Turkey
Bibliographic record
Abstract
Children born in the first months of the same year are physically more advantageous than those born in the last months, and this advantage decreases as the athletes gets older. Athletes born in the last months of the year and unsuccessful may leave their careers at a young age. The aim of the study was to examine the relationship between tournament success and birth months in 11-year-old Freestyle and Greco-Roman style wrestlers. It was hypothesized that wrestlers born in the first months of the year would be more successful than those born in the last months. Tournament ranking and birth date information of 327 wrestlers who participated in the Turkey 11-Year-Old Male Freestyle and Greco-Roman Style Wrestling Tournament were used. In order to examine the relationship between athlete success and birth months, Chi-Square analysis was performed by grouping birth months into four quarters of the year. It was observed that the success rankings of both Freestyle and Greco-Roman style wrestlers decreased from the first quarter to the last quarter of the year (Freestyle: χ2 = 42.749, df = 3, p = .000; Greco-Roman style: χ2 = 25.627, df = 3, p = .000). It is thought that birth months should be given importance when grouping at young ages, especially in sports branches such as wrestling, where physical contact is high.
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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 | 0.001 | 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".