{"id":"W4388894989","doi":"10.2139/ssrn.4633517","title":"Excess Deaths in China During SARS-Cov-2 Viral Waves in 2022-2023","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Centre for Global Health Research","funders":"","keywords":"Virology; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); China; Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Sars virus; Medicine; Internal medicine; Geography; Outbreak; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0004740687,0.0003830023,0.0002818314,0.001085772,0.0003350137,0.0006883282,0.000376665,0.0004680779,0.003949179],"category_scores_gemma":[0.0009670836,0.0002676155,0.0006665705,0.001373178,0.000169987,0.000471752,0.0005963995,0.0004633841,0.0004342267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009279665,"about_ca_system_score_gemma":0.001501044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06330322,"about_ca_topic_score_gemma":0.06953928,"domain_scores_codex":[0.9997383,0.00003239854,0.00001996548,0.00005525513,0.00003536767,0.0001185986],"domain_scores_gemma":[0.9995285,0.00005071144,0.0001567829,0.00003391151,0.00008932072,0.0001407371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004458512,0.00003004493,0.9852651,0.00005785835,0.0001873483,0.0003051462,0.0002176204,0.001320368,0.0004257917,0.0009470832,0.004545121,0.006252741],"study_design_scores_gemma":[0.0000145363,0.00002825495,0.9962147,0.00000927293,0.00004618944,0.00006727418,0.0001915126,0.001896127,0.00009121747,0.0002043415,0.001227725,0.000008806847],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889292,0.0009314391,0.0002628965,0.0007911365,0.00006228484,0.0000115417,0.006982227,0.00002877135,0.002000487],"genre_scores_gemma":[0.9932035,0.0003361048,0.00005973624,0.00007105378,0.00004471061,0.00001218784,0.003842652,0.00000623715,0.002423798],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06330322,"threshold_uncertainty_score":0.1258695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1305771219876175,"score_gpt":0.4076680989709905,"score_spread":0.277090976983373,"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."}}