{"id":"W3196553362","doi":"10.3233/sji-210871","title":"Estimating excess mortality in Canada during the COVID-19 pandemic: Statistical methods adapted for rapid response in an evolving crisis","year":2021,"lang":"en","type":"article","venue":"Statistical Journal of the IAOS","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Crisis response; Econometrics; Medicine; Virology; Political science; Economics; Outbreak; Internal medicine; Infectious disease (medical specialty); Public relations","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02718337,0.001094194,0.0008797902,0.004134025,0.001518966,0.002315799,0.002087136,0.0006547057,0.00209877],"category_scores_gemma":[0.09432685,0.0005883488,0.001109179,0.006496143,0.001323994,0.0009027107,0.001831264,0.002157302,0.0003538044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01708135,"about_ca_system_score_gemma":0.04366746,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.940636,"about_ca_topic_score_gemma":0.9327386,"domain_scores_codex":[0.9891791,0.007392996,0.0004429002,0.0007438764,0.001837518,0.0004035044],"domain_scores_gemma":[0.9603603,0.0269611,0.002550923,0.002956194,0.006638202,0.0005332411],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003778106,0.0001566042,0.2792359,0.0006277115,0.001299477,0.0004859823,0.003094393,0.3248883,0.001059558,0.07841498,0.0406677,0.2696916],"study_design_scores_gemma":[0.000167561,0.0001973512,0.1700376,0.0004497519,0.0003121648,0.0001574211,0.003128352,0.7365113,0.001972927,0.04377184,0.04306532,0.0002283091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07547849,0.001340919,0.8977259,0.00441328,0.000207887,0.001712639,0.0114133,0.00186416,0.005843396],"genre_scores_gemma":[0.3877484,0.001513371,0.5957327,0.0008469833,0.0001331594,0.002084787,0.007244788,0.0004909323,0.004204863],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05936396,"threshold_uncertainty_score":0.1437611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3473294308277915,"score_gpt":0.5246717628312118,"score_spread":0.1773423320034203,"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."}}