{"id":"W3036026545","doi":"10.1101/2020.06.19.20136069","title":"Global years of life lost to COVID-19","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Oxford; Economic and Social Research Council; “la Caixa” Foundation","keywords":"Years of potential life lost; Coronavirus disease 2019 (COVID-19); Demography; Demographics; Quarter (Canadian coin); 2019-20 coronavirus outbreak; Life expectancy; Pandemic; Medicine; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Geography; Environmental health; Disease; Population; Virology; Outbreak; Infectious disease (medical specialty); Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001192107,0.0004555369,0.0004105892,0.001729955,0.0001923085,0.001303808,0.0003204216,0.0003704338,0.01318113],"category_scores_gemma":[0.005313833,0.0001169607,0.0008564362,0.002685343,0.0002891008,0.00104958,0.001079372,0.0007858022,0.004655483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007008371,"about_ca_system_score_gemma":0.0004336406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003651981,"about_ca_topic_score_gemma":0.002517727,"domain_scores_codex":[0.9993004,0.0002002197,0.00005909139,0.0001447374,0.0001878463,0.0001077607],"domain_scores_gemma":[0.998925,0.0002522239,0.0003317053,0.00009516203,0.0002751224,0.0001207761],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0011675,0.00006639383,0.2578936,0.00229449,0.001842242,0.0003397474,0.001226524,0.007478715,0.0006412728,0.02278337,0.4290749,0.2751912],"study_design_scores_gemma":[0.00008519618,0.000512887,0.4872441,0.001541227,0.0005500994,0.001780794,0.001179239,0.002511281,0.0007620364,0.01199086,0.4917629,0.00007941233],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.2757388,0.05869696,0.009785345,0.01241053,0.003149557,0.00015235,0.5022895,0.001218463,0.1365585],"genre_scores_gemma":[0.6775492,0.03504083,0.004954035,0.003199609,0.001080471,0.000421738,0.2423135,0.000419167,0.03502134],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01318113,"threshold_uncertainty_score":0.04409522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3451479936606384,"score_gpt":0.4554296068294579,"score_spread":0.1102816131688195,"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."}}