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Record W2908920177 · doi:10.31501/rbpe.v8i1.8319

Efeitos da prática de musculação nos estados de humor de jovens aprendizes

2018· article· pt· W2908920177 on OpenAlexaff
Cristina Carvalho de Melo, Tatiana Lima Boletini, Camila Cristina Fonseca Bicalho, Varley Teoldo da Costa, Franco Noce

Bibliographic record

VenueRevista Brasileira de Psicologia do Esporte · 2018
Typearticle
Languagept
FieldHealth Professions
TopicOccupational Health and Burnout
Canadian institutionsHumber Polytechnic
Fundersnot available
KeywordsHumanitiesPsychologyPhysicsArt

Abstract

fetched live from OpenAlex

Objetivo: verificar os efeitos da atividade física nos estados de humor no ambiente de trabalho. Método: Foram avaliados 56 Jovens Aprendizes de uma empresa sendo 42 do sexo masculino e 14 do sexo feminino. O instrumento utilizado para coleta dos dados referentes à avaliação do estado de humor foi o questionário BRAMS, que contém 24 itens organizados em seis dimensões: tensão, depressão, raiva, vigor, fadiga e confusão. Cada item é avaliado em uma escala de cinco pontos (0 = nada a 4 = extremamente), sendo o somatório de cada dimensão (escore bruto) interpretado através de uma tabela percentil. Resultados: Os valores médios das variáveis emocionais nas diferentes situações avaliadas revelam que as dimensões negativas (tensão, depressão, raiva e confusão) apresentaram diminuição nos dias com prática de musculação, apenas para a dimensão negativa “fadiga” não houve diminuição; a dimensão positiva “vigor” permaneceu inalterada. Conclusão: A partir dos resultados encontrados nesse estudo, é possível concluir que uma sessão de musculação, modifica de forma positiva o estado de humor dos sujeitos.

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)0.005
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.069
GPT teacher head0.418
Teacher spread0.349 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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