{"id":"W3177512113","doi":"10.1101/2021.07.12.21260387","title":"Lessons learned and lessons missed: Impact of the Covid-19 pandemic on all-cause mortality in 40 industrialised countries prior to mass vaccination","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"British Heart Foundation; Wellcome Trust; U.S. Environmental Protection Agency","keywords":"Pandemic; Preparedness; Demography; Coronavirus disease 2019 (COVID-19); Mortality rate; Geography; Population; Excess mortality; Socioeconomics; Medicine; Political science; Disease; Economics; Infectious disease (medical specialty)","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":[0.02927729,0.001355087,0.001355783,0.001164411,0.0005585324,0.003220731,0.001818519,0.002086911,0.001634526],"category_scores_gemma":[0.04432864,0.0007420647,0.002446526,0.001435226,0.001395946,0.003672746,0.002590168,0.003862369,0.0002849548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002177712,"about_ca_system_score_gemma":0.002995833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04219685,"about_ca_topic_score_gemma":0.03734855,"domain_scores_codex":[0.9920522,0.005599821,0.0003148889,0.0008209781,0.0007194849,0.0004925664],"domain_scores_gemma":[0.9865465,0.009272417,0.001076899,0.0008002866,0.001303469,0.001000458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007003333,0.0001943041,0.5965061,0.0008857607,0.002496782,0.001205152,0.002417211,0.2967499,0.0007185196,0.003603447,0.006425624,0.0880969],"study_design_scores_gemma":[0.0002261781,0.001254736,0.560258,0.003176952,0.001557862,0.0006331862,0.009443372,0.3691489,0.00148102,0.03860979,0.01369589,0.0005142095],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9277377,0.008245561,0.01137083,0.04354663,0.0005725248,0.0001018494,0.002170283,0.0001650608,0.006089476],"genre_scores_gemma":[0.9885045,0.0034427,0.004822283,0.001779577,0.000217255,0.00003016752,0.0008173267,0.00003764965,0.0003484293],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04219685,"threshold_uncertainty_score":0.1548349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3733787195345076,"score_gpt":0.4612970915033463,"score_spread":0.08791837196883873,"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."}}