{"id":"W3025300857","doi":"10.1049/ccs.2020.0017","title":"Predicting COVID‐19 trends in Canada: a tale of four models","year":2020,"lang":"en","type":"article","venue":"Cognitive Computation and Systems","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto; Lakehead University; University of Windsor","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Logistic regression; Pandemic; Econometrics; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Turning point; Regression; Regression analysis; Demography; Statistics; Geography; Computer science; Medicine; Economics; Mathematics; Virology; Period (music); Sociology","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":[0.001723337,0.001159252,0.0006536377,0.001159954,0.001338904,0.002138247,0.001797244,0.0007916534,0.001714851],"category_scores_gemma":[0.004631313,0.0004111971,0.0008073567,0.001049714,0.0008924999,0.001346875,0.001281428,0.002066872,0.0002692491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01170907,"about_ca_system_score_gemma":0.01023717,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8638796,"about_ca_topic_score_gemma":0.8122953,"domain_scores_codex":[0.9995166,0.0001433923,0.00002068043,0.0001074981,0.00007294995,0.0001388472],"domain_scores_gemma":[0.9985079,0.0006776177,0.0001005817,0.00005375875,0.0004901506,0.0001699089],"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":[0.0004024775,0.0001510282,0.1108633,0.0001890805,0.000471316,0.0002920901,0.000510284,0.7537433,0.0003920441,0.03891917,0.02012035,0.07394557],"study_design_scores_gemma":[0.00002361879,0.00003755537,0.007469468,0.0000462076,0.00009343587,0.00002806361,0.0002847306,0.972539,0.0001776642,0.01669545,0.00256494,0.00003981005],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7217128,0.01055253,0.1593217,0.06371845,0.0007350601,0.0002404933,0.006969459,0.001303728,0.03544584],"genre_scores_gemma":[0.9658849,0.002384719,0.02266464,0.0009298107,0.0001130427,0.00004788431,0.002071463,0.00005854997,0.005845016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1361204,"threshold_uncertainty_score":0.273844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1163314383346385,"score_gpt":0.3323212106462635,"score_spread":0.215989772311625,"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."}}