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Record W6981777398

Exposición ocupacional al formaldehído y riesgo de cáncer de pulmón: revisión sistemática y meta-análisis

2023· dissertation· es· W6981777398 on OpenAlexaboutno aff

Bibliographic record

Venuerenati · 2023
Typedissertation
Languagees
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsnot available
Fundersnot available
KeywordsPoison controlOccupational exposureOccupational safety and health
DOInot available

Abstract

fetched live from OpenAlex

Objetivo: Describir la asociación de la exposición ocupacional al formaldehído
\nen el riesgo de cáncer de pulmón mediante la síntesis de evidencia en la revisión
\nsistemática y metaanalisis.
\nMétodos: Se realizó de una revisión sistemática. Pubmed, Scopus, Web of
\nScience y EMBASE son las bases de datos bibliográficas en las que se realizó
\nla búsqueda. Se incluyeron todos aquellos trabajos que cumplieron con los
\nsiguientes criterios: 1) Estudios observacionales (cohorte o caso control); 2)
\nEstudios que evaluaron la asociación de la exposición ocupacional al
\nformaldehído en el riesgo de cáncer de pulmón. Al inicio se obtuvo 336 estudios 
\nen diferentes bases de datos. Se aplicó una estrategia de búsqueda con palabras 
\nclave ("lung cancer") AND ("occupational exposure") AND (formaldehyde). La 
\nherramienta Newcastle Ottawa Scale (NOS) fue utilizada para la evaluación de
\nriesgo de sesgo.
\nResultados: Diez estudios se incluyeron en la revisión sistemática. Se encontró
\nque el formaldehído aumenta la posibilidad de cáncer de pulmón comparado con
\nel control (OR 2.95; IC95% 2.33-3.74; p=0.0001).
\nConclusión: Se encontró una fuerte asociación entre la exposición ocupacional
\nal formaldehído y el riesgo de cáncer de pulmón

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.183
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.035
GPT teacher head0.302
Teacher spread0.268 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2023
Admission routes1
Has abstractyes

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