Influencia del lugar de origen en la utilización de pruebas de cribado de cáncer ginecológico en España
Bibliographic record
Abstract
OBJECTIVE: To assess the association between geographic origin and the use of screening cervical smears and mammograms. METHODS: Data was obtained from the 2006 Spanish National Health Survey that included 13,422 females over 16 years of age. The dependent variable was use of screening mammograms and cervical smears in the past 12 months. The measure of association (odds ratio and its related 95% confidence interval) was estimated using logistic regression. RESULTS: African women were 0.36 (95% CI 0.21,0.62), Eastern European 0.40 (95%CI 0.22;0.74), Western European, American and Canadian 0.60 (95%CI 0.43,0.84), and Central and South American 0.64 times (95%CI 0.52, 0.81) less likely to undergo a mammogram compared with the general population of Spain. In regard to cervical cancer screening, Eastern European women were 0.38 (95%CI 0.28,0.50), African 0.47 (95%CI 0.33,0.67) and Western European, American and Canadian 0.61 times (95%CI 0.46, 0.81) less likely to undergo cervical smears. These associations were independent of age, socioeconomic condition, health status and health insurance coverage. CONCLUSIONS: Immigrant women use less screening programs than native Spanish women. This finding may suggest difficult access to prevention programs.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".