Laudos de mamografia de rastreamento no Brasil, uma análise da cobertura e dos indicadores socioeconômicos
Bibliographic record
Abstract
O objetivo do estudo é avaliar a cobertura da mamografia (MMG) de rastreio das macrorregiões do Brasil, e a correlação dos laudos mamográficos com os indicadores socioeconômicos estaduais. Trata-se de um estudo retrospectivo, do tipo ecológico que analisa os laudos das MMG de rastreio no Brasil, de mulheres entre 50 e 69 anos, dos anos de 2013 a 2020. Os dados foram obtidos do Sistema de Informação do Câncer (SISCAN), plataforma DATASUS, e organizados em um banco de dados no programa Excel. Os resultados mostraram uma cobertura nacional de 12,07%, no período estudado, o sul obteve a maior cobertura dentre as macrorregiões, de 17,07%, seguido do nordeste, com 12,56%. O coeficiente de correlação de Pearson entre o percentual de laudos suspeitos de câncer de mama e o Índice de Desenvolvimento Humano Municipal (IDHM) foi - 0,0349. Como principais conclusões temos que o rastreio está aquém das metas e sua cobertura é desigual entre as macrorregiões. A correlação nula, pode estar relacionada aos números pouco expressivos de exames realizados e as limitações dos indicadores.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".