Defunciones por COVID-19: distribución por edad y universalidad de la cobertura médica en 22 países
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Relate standardized age distribution of COVID-19 deaths in 22 countries in the Americas and Europe to different indicators of population characteristics and health systems. METHODS: Distributions of COVID-19 deaths by age group in 22 countries of the Americas and Europe were standardized based on the age pyramid of the world's population. Correlations were calculated between the standardized proportion of people aged <60 years among the deceased and each of six indicators. RESULTS: Standardization based on the world age pyramid revealed considerable differences in age distribution among countries; the proportion of people aged <60 years was higher in Latin America and the United States than in Canada or Western Europe. The standardized proportion of people aged <60 years among persons who died of COVID-19 is strongly correlated to the existence of universal quality medical coverage (r=-0.92, p<0.01). This relationship remained significant after being adjusted for the other indicators. CONCLUSION: We propose that weaknesses in medical coverage of the population may have created higher case-fatality in populations aged <60 years in Latin America and the United States.
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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 | 0.004 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it