EFEITO DA IDADE RELATIVA NOS CAMPEONATOS ESTADUAIS DE FUTEBOL PROFISSIONAL
Bibliographic record
Abstract
The objective of this study was to verify if the effect of relative age (EIR) influences the participation of soccer playersin high-performance competitions, in an analysis done in the semi-finalists of the Carioca and Paulista football championships.The birth dates of 689 players were collected. The information was acquired from the register of players published on the websiteof the Federation of Soccer of the state of Rio de Janeiro (www.fferj.com.br) and of the Sao Paulo Football Federation(www.futebolpaulista.com.br). The birth dates of the players were separated in quarters and the first quarter: born in the monthsJanuary, February and March; 2nd quarter: born in April, May and June; 3rd quarter: born in July, August and September; 4thquarter: born in the months of October, November and December, to be then compared so that it could be concluded if there ispredominance in the choice of players who were born in the first months of the year. The procedure used was descriptive statisticswhere the data were analyzed and the population data profiles were presented. The chi-square test was used to compare thedifferences between quartiles. We adopted a significance level of p <0.05. The result of this study concluded that the effect ofrelative age (EIR) influences the transition of soccer players to the base and participation in high-income competitions. A highernumber of players were observed, with birth dates for the first semester (69.7%) and a more significant volume of births betweenJanuary and March (41.2%).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".