Estimaciones de esperanza de vida al nacer en áreas menores de la región pampeana
Bibliographic record
Abstract
Resumen Para determinar el nivel y las diferencias de mortalidad entre los departamentos de Argentina entre 2009 y 2011, aplicamos y comparamos estimaciones de esperanza de vida al nacer en la región pampeana. Usamos tres métodos de suavizado: un enfoque bayesiano, un método de tablas de vida relacional y un enfoque indirecto de los niveles de mortalidad, en los departamentos de la región. Los resultados permiten ordenar los departamentos de las provincias de acuerdo con su esperanza de vida (con intervalos de confianza estadísticos) y calcular indicadores de desigualdad intraprovincial. Encontramos que la provincia de Buenos Aires fue la de mayor dispersión medida por el rango y el coeficiente de variación. El artículo contribuye a la discusión y aplicaciones de modelos alternativos para estimar la mortalidad local y proporciona la posibilidad de analizar los patrones espaciales para comprender los resultados demográficos individuales relacionados con características geográficas y socioeconómicas asociadas.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 teacher head, 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".