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Record W3008516144 · doi:10.53357/gdbc6038

Asma e Transtornos Psiquiátricos: Uma Revisão da Literatura

2019· article· pt· W3008516144 on OpenAlexaff
Ana Alice Carneiro Da Fonseca, Cintia de Freitas Andrade, Fernanda Blanco Vázquez, Isadora Moura Fajardo

Bibliographic record

VenueDiversitates International Journal · 2019
Typearticle
Languagept
FieldHealth Professions
TopicOccupational Health and Burnout
Canadian institutionsImpact
Fundersnot available
KeywordsMedicineHumanitiesArt

Abstract

fetched live from OpenAlex

Asma e Transtornos Mentais são condições comuns e com grande morbimortalidade associada. Há evidências de que haja relação entre eles. Neste estudo revisamos narrativamente a prevalência de transtornos mentais em pacientes com asma; os efeitos da comorbidade psiquiátrica sobre o desfecho da asma; e o impacto do tratamento dessas condições. Foi realizada busca no PubMed e no Google Acadêmico usando as palavras chave asthma e mental disorders. Resultados: Transtornos psiquiátricos são mais prevalentes em pacientes com asma quando comparados à população geral e associam-se a pior controle dos sintomas, maiores taxas de internação, pior qualidade de vida e trazem maior encargo ao sistema de saúde. Conclusão: Pacientes com asma, sobretudo aqueles de difícil controle, devem ser avaliados quanto à presença de doença psiquiátrica. Entretanto, são necessários mais estudos para compreender o impacto do tratamento da comorbidade psiquiátrica sobre a asma.Palavras chave: asma, transtornos psiquiátricos, revisão narrativa

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)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0080.009
Science and technology studies0.0020.003
Scholarly communication0.0050.006
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.044
GPT teacher head0.400
Teacher spread0.356 · 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 designSystematic review
Domainnot available
GenreReview

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
Published2019
Admission routes1
Has abstractyes

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