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Efeito da idade relativa no Campeonato Brasileiro de Basquete: Categoria sub-15

2017· article· en· W2780649768 on OpenAlexaboutno aff
Hélder Zimmermann Oliveira, Dilson Borges Ribeiro, Jéferson Macedo Vianna, Francisco Zacaron Werneck

Bibliographic record

VenueBrazilian Journal of Kinanthropometry and Human Performance · 2017
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsnot available
FundersUniversidade Federal de Ouro PretoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsBasketballChampionshipAthletesDemographyQuarter (Canadian coin)QuartileGeographyHumanitiesPsychologyMedicineSociologyPhysical therapyArtConfidence interval

Abstract

fetched live from OpenAlex

In sport, the relative age effect (RAE) refers to the advantages of participation and performance that athletes born in the first months of the selection year have in relation to those within the same age category. The aim of the present study was to investigate the RAE in athletes of the Brazilian Basketball Championship of the U-15 category in 2015, analyzing differences between sexes, geographic region, competitive level and performance of teams. The information of teams and the birth quarter (quartile) of 530 basketball players were obtained through the website of the Brazilian Basketball Confederation. The results showed greater representation of male athletes born in the first months of the year, the first and second divisions, of the Southeastern, Northern and Mid-Western regions and in female medalists. It was concluded that the RAE is present in Brazilian U-15 male basketball players, being higher in athletes of higher competitive level, particularly in the Southeastern, Northern and Mid-Western regions of Brazil. In addition, RAE proved to be associated with the winning of women’s medals.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.024
GPT teacher head0.322
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2017
Admission routes1
Has abstractyes

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