{"id":"W3020177603","doi":"10.1101/2020.04.17.20069161","title":"Mortality from COVID-19 in 12 countries and 6 states of the United States","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"COVID-19 and healthcare impacts","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Government of Canada; Health Canada; Centre for Global Health Research; University of Toronto","funders":"Canadian Institutes of Health Research; University of Toronto","keywords":"Coronavirus disease 2019 (COVID-19); Demography; China; Geography; Mortality rate; Population; Medicine; Socioeconomics; Economics; Disease","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005595421,0.0002635204,0.0007142274,0.0001696678,0.00005716648,0.00002743058,0.0002131855,0.0002333027,0.0001244031],"category_scores_gemma":[0.001859344,0.0001842379,0.00008646194,0.0002635134,0.0003043208,0.00002750533,0.0004631818,0.0007785324,0.000003280841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002659734,"about_ca_system_score_gemma":0.00194741,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09895495,"about_ca_topic_score_gemma":0.01117975,"domain_scores_codex":[0.9980047,0.0002490366,0.0005745837,0.0004505007,0.0004521006,0.0002690742],"domain_scores_gemma":[0.9976609,0.0008323804,0.0002896764,0.0006506416,0.0001190614,0.0004473588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002467319,0.00004635537,0.9867285,0.002990898,0.0001055322,0.00007045258,0.0081423,0.0002251826,0.00009239551,0.00007284137,0.001218059,0.00006069766],"study_design_scores_gemma":[0.0009938239,0.00007838853,0.956187,0.0005313454,0.0001455443,0.000002117281,0.0006484235,0.00112184,0.0004534458,0.008263431,0.03141414,0.000160545],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9349641,0.001118842,0.00009398559,0.06170037,0.0002235226,0.0007486395,0.001062497,0.0000592719,0.00002873097],"genre_scores_gemma":[0.9723483,0.003578037,0.00004706004,0.02322618,0.00009715147,0.00002124107,0.0006218716,0.00002611114,0.00003402881],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0877752,"threshold_uncertainty_score":0.9070452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.128956727158278,"score_gpt":0.4075241036640327,"score_spread":0.2785673765057547,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}