5https://doi.org/10.5569/1134-7147.76.01 ZERBITZUAN 76MARTXOA·MARZO 2022 Impacto de la COVID-19 en los centros residenciales de Euskadi: un análisis multinivel de la importancia de los factores de riesgo relativos al centro
Bibliographic record
Abstract
El presente artículo describe el análisis multinivel realizado en el marco de un reciente estudio que concluye que el centro residencial y sus características pueden explicar hasta un 55 % de las diferencias en el riesgo de contagio por SARS-CoV-2 entre personas que vivían en centros residenciales para personas mayores entre marzo y octubre de 2020 en Euskadi. El análisis, para el que se pudieron analizar datos de Osakidetza de más de 20.000 personas atendidas en esos centros, revela que las personas contagiadas tuvieron entre un 22 % y un 57 % más de riesgo de fallecer en el periodo de estudio. Los resultados indican que la intervención preventiva a nivel de centro puede resultar efectiva, pero que se necesita seguir investigando para conocer los factores específicos del centro que deben modificarse para reducir los contagios. El impacto de las características estructurales de los centros y la organización del personal son aspectos que habría que analizar de forma prioritaria.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.258 | 0.106 |
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".