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Record W2224853370 · doi:10.33233/fb.v9i3.1643

Prevalência de lombalgia em praticantes de musculação

2017· article· pt· W2224853370 on OpenAlexaboutno aff
Sérgio Medeiros Pinto

Bibliographic record

VenueFisioterapia Brasil · 2017
Typearticle
Languagept
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhysical activityMedicinePhysical therapyArt

Abstract

fetched live from OpenAlex

O propósito deste estudo foi estimar a prevalência de dor lombar entre praticantes de musculação, bem como estratificar aqueles que acusam este sintoma quanto ao grau de intensidade da dor (severa, moderada e suave). A amostra foi composta de 260 indiví­duos do sexo masculino, com idade média de 27,6 anos (± 6,8), praticantes de musculação em academias do bairro do Méier do Rio de Janeiro. O estudo é do tipo descritivo transversal e utilizou como variável discricionária a presença de dor lombar. Os dados foram coletados através do Quebec Back Pain Disability Scale. Como resultado, encontramos que a prevalência de lombalgia entre os participantes foi de 47,3% (n = 123), variando quanto í sua intensidade entre suave (39,8% dos praticantes), moderada (51,2%), severa (8,9%) e apresentando mensalmente (36,6%) as maiores freqüências de queixa da dor. Entre aqueles que alegaram sentir dor 57,7 % disseram não sentir dor enquanto praticam musculação. Outro dado importante revela que 68,3% dos que sentem dor não perderam nenhum dia de trabalho devido a esta algia.Palavras-chave: musculação, prevalência, lombalgia.Â

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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.321
Teacher spread0.304 · 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

Citations3
Published2017
Admission routes1
Has abstractyes

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