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PMC:7786642 / 14114-14887 JSONTXT

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LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
136 418-427 Disease denotes mortality MESH:D003643
137 620-629 Disease denotes mortality MESH:D003643

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T112 0-231 Sentence denotes In order to propagate the uncertainty resulted from the sampling we used for the downscaling, we fitted the models over 100 downscaled samples and then performed Bayesian model averaging to combine the estimates (Gómez-Rubio et al.
T113 232-238 Sentence denotes 2020).
T114 239-362 Sentence denotes We performed a complete case analysis since for only 1.1% of the cases information about age, sex and ethnicity is missing.
T115 363-576 Sentence denotes We report results as posterior median of % increase in mortality risk for every 1 μg/m3 increase in the air-pollutants, 95% credible intervals (CrI) and posterior probability that the estimated effect is positive.
T116 577-773 Sentence denotes We also report posterior median of spatial mortality relative risks (exponential of the spatial autocorrelation term) and posterior probabilities that the spatial relative risks are larger than 1.