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Combinação de indicadores negativos da aptidão física e fatores associados em adolescentes

2017· article· en· W4255046109 on OpenAlexaboutno aff
Tiago Rodrigues de Lima, Diego Augusto Santos Silva

Bibliographic record

VenueBrazilian Journal of Kinanthropometry and Human Performance · 2017
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Regulation
Canadian institutionsnot available
Fundersnot available
KeywordsPhysical fitnessAerobic exerciseDemographyFitness testLogistic regressionCardiovascular fitnessMultinomial logistic regressionPsychologyMedicineGerontologyPhysical therapyStatisticsMathematics

Abstract

fetched live from OpenAlex

DOI: http://dx.doi.org/10.5007/1980-0037.2017v19n4p436 Inadequate levels in health-related physical fitness components are associated with early cardiovascular mortality in adult life. The aim of this study was to analyze the association between clusters of negative physical fitness indicators with sociodemographic and lifestyle variables in adolescents. The survey was conducted with 866 students (14-19 years) from public schools of São José, Santa Catarina, Brazil. Aerobic fitness was assessed by the modified Canadian aerobic fitness test; muscle strength was measured by handgrip dynamometer; flexibility was assessed by the sit-and-reach test; body fat was measured by the sum of triceps and subscapular skinfolds. Sociodemographic and lifestyle variables were verified by questionnaire. The simultaneity of behaviors was evaluated by the ratio between observed and expected prevalence of inadequate physical fitness levels. The combination of negative physical fitness indicators was analyzed through multinomial logistic regression. The prevalence observed for the simultaneity of four negative physical fitness indicators was 30% higher than expected. Female adolescents were more susceptible to the presence of two, three and four negative physical fitness indicators. Adolescents who presented risk behavior in relation to screen time were more likely to present one, three and four negative physical fitness indicators. Female gender and risk behavior in relation to screen time were factors associated with the simultaneity of negative physical fitness indicators.

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 score0.005
Threshold uncertainty score0.009

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 head0.062
GPT teacher head0.442
Teacher spread0.381 · 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".

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Citations2
Published2017
Admission routes1
Has abstractyes

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Same venueBrazilian Journal of Kinanthropometry and Human PerformanceSame topicHealthcare RegulationFrench-language works237,207