Monitoring the cluster of high-risk mortality areas in the southwest of Spain
Bibliographic record
Abstract
Inspired by a previous study showing a striking geographical mortality clustering, not attributable to chance, in the south-western region of Spain in 1987-1995, the authors have conducted an ecological study of time trends in all-cause mortality risk between 1987-1995 and 1996-2004 in 2,218 small areas of Spain. To identify high-risk areas, age-adjusted relative risks for each area, stratified by sex and time period, were computed using a Bayesian approach. Areas of high-risk in both periods, or in the second period only, were identified. Annual excess mortality and percentage of people living in these high-risk areas, again stratified by sex and time period, were estimated. The cluster of high mortality risk areas identified in the southwest of Spain during 1987-1995 persisted in the period 1996-2004 with an increase in the number of high-risk areas and in annual excess of mortality. These increases showed a gender difference, being more pronounced in women.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".