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AVALIAÇÃO DE RISCOS E SEGURANÇA EM CANTEIROS DE OBRAS CIVIS

2023· article· pt· W4388760781 on OpenAlexaff
Paulo Romero de Farias Neves, Gilmar Fernando De Melo Júnior

Bibliographic record

VenueRevista Foco · 2023
Typearticle
Languagept
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsHumanitiesPhysicsPhilosophy

Abstract

fetched live from OpenAlex

Este estudo tem por base os riscos e fatores de segurança aos trabalhadores em canteiros de obras da construção civil. Assim, o objetivo deste estudo e explorar a legislação e os conceitos que envolvem o tema de segurança do trabalho e avaliar o cumprimento e eficiência de atendimento de Normas Regulamentadoras relacionadas à saúde e segurança dos trabalhadores em quatro obras do ramo de construção civil na cidade de Rio Verde, Goiás. Para tanto, elaborou-se um check-list com itens da NR-04, NR-06, NR-10, NR-18 e NR-35 como instrumento para realização de vistorias em canteiros de obras em fases construtivas diferentes, onde foram coletados os dados para posterior avaliação e discussão. A partir do estudo de campo aliado à base teórica, verificou-se que os trabalhadores estão submetidos a vários riscos à saúde devido a não adoção de medidas preventivas e a criação de uma cultura de segurança, pois, nem todas as empresas seguem à risca o que é determinado por lei.. Dessa forma, é indispensável o comprometimento dos empregadores e trabalhadores para assegurar a segurança ocupacional.

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)0.004
metaresearch head score (Gemma)0.013
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 score0.071
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0050.003
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.115
GPT teacher head0.478
Teacher spread0.363 · 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
Published2023
Admission routes1
Has abstractyes

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