{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00101549,0.0001870788,0.0002049885,0.00184555,0.001383776,0.003723486,0.0003793209,0.00107539,0.01062612],"category_scores_gemma":[0.004163841,0.0001110056,0.0002223941,0.002028715,0.004222221,0.005575133,0.001531861,0.001815372,0.0006156006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003075626,"about_ca_system_score_gemma":0.0009708887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007962872,"about_ca_topic_score_gemma":0.01040073,"domain_scores_codex":[0.999597,0.0001548826,0.00001561999,0.00003967769,0.00009920695,0.00009355482],"domain_scores_gemma":[0.9985008,0.0007045743,0.0002356686,0.0001044175,0.0001704379,0.000284066],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001502944,0.00002400304,0.00826363,0.0003297159,0.00002701057,0.0002370158,0.006492377,0.0008480359,0.0002489822,0.8512919,0.06319869,0.06888833],"study_design_scores_gemma":[0.00001477652,0.00007601221,0.02614305,0.001149344,0.00002284903,0.0004922668,0.009891367,0.0007011471,0.0002544557,0.2155558,0.7456534,0.00004551905],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.09093741,0.06964345,0.004254073,0.1083314,0.006228823,0.00002636871,0.001117029,0.00008879711,0.7193727],"genre_scores_gemma":[0.9214112,0.03815864,0.001015065,0.008172827,0.004004142,0.00001898261,0.0005344318,0.00008477175,0.0265999],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01062612,"threshold_uncertainty_score":0.03554785,"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."}}