{"id":"W3158960453","doi":"10.15173/sciential.v1i5.2549","title":"COVID-19 vs. History’s Pandemics","year":2020,"lang":"en","type":"article","venue":"Sciential - McMaster Undergraduate Science Journal","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Pandemic; Infographic; Coronavirus disease 2019 (COVID-19); Outbreak; Context (archaeology); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Geography; Virology; History; Medicine; Computer science; Infectious disease (medical specialty); Disease","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004222755,0.0003233009,0.0005304905,0.0008410434,0.001068196,0.0008166073,0.001934573,0.0001168126,0.001944959],"category_scores_gemma":[0.004264378,0.0003345776,0.0002628602,0.001880028,0.001301345,0.002190751,0.0004458527,0.0007508008,0.0009656571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003220187,"about_ca_system_score_gemma":0.003148217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001251848,"about_ca_topic_score_gemma":0.00001711723,"domain_scores_codex":[0.9959131,0.00004717607,0.001118564,0.001110147,0.0005694284,0.001241587],"domain_scores_gemma":[0.9952745,0.0000663314,0.0009345009,0.0004099337,0.000154429,0.003160281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007009147,0.0005260244,0.1431347,0.0003450135,0.0002226214,0.0003638323,0.03072194,0.01233871,0.0192946,0.1934651,0.5892522,0.00963441],"study_design_scores_gemma":[0.002143548,0.0003417146,0.001684696,0.00002005712,0.00001930762,0.0002566687,0.0002836897,0.02273554,0.0001680013,0.05672389,0.9148751,0.000747717],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1258768,0.003527431,0.3574316,0.426622,0.02263928,0.001183622,0.000170866,0.0005681278,0.06198036],"genre_scores_gemma":[0.9490537,0.0001590222,0.001845672,0.04527389,0.000735011,0.000003669548,0.000002592544,0.00003571739,0.00289073],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8231769,"threshold_uncertainty_score":0.9999107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09831006144433577,"score_gpt":0.284090305139925,"score_spread":0.1857802436955892,"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."}}