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Record W4402095091 · doi:10.34119/bjhrv7n4-434

Epidemiologia do Câncer de Colo de Útero no Norte do Brasil entre 2011 e 2021: um estudo ecológico

2024· article· pt· W4402095091 on OpenAlexaff
Maria Clara Amorim Freitas, Valeska Alves Dutra, Igor Vitor Oliveira da Graça, Guilherme Batalha

Bibliographic record

VenueBrazilian Journal of Health Review · 2024
Typearticle
Languagept
FieldMedicine
TopicWomen's cancer prevention and management
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

Objetivo: Apresentar a epidemiologia do Câncer de Colo de Útero (CCU) no Norte do Brasil entre 2011 e 2021. Métodos: Este estudo adota uma perspectiva ecológica de análise temporal. As informações epidemiológicas sobre ano de notificação, faixa etária, anos potenciais de vida perdidos e estado de notificação foram coletadas em Outubro de 2023 no site do Instituto Nacional do Câncer e Instituto Brasileiro de Geografia e Estatística. Resultados: O Norte do Brasil foi a região com mais mortes (8.773). Houve um crescimento tanto do número absoluto de mortes quanto da taxa de mortalidade (de 7,74 em 2011 para 9,19 em 2021). A taxa de mortalidade nos 11 anos analisados foi de 122 por 100.000 mulheres. Conclusão: Foi possível uma compreensão da população mais afetada pelo CCU, informação útil para a criação de médicas capazes de auxiliar o planejamento em saúde.

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)0.002
metaresearch head score (Gemma)0.006
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: none
Teacher disagreement score0.161
Threshold uncertainty score0.320

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.376
Teacher spread0.343 · 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
Published2024
Admission routes1
Has abstractyes

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