{"id":"W4413631434","doi":"10.64628/aam.rf5f6ve3p","title":"A university course on pandemics: What we learned when 80 experts, 300 alumni and 600 students showed up","year":2021,"lang":"en","type":"article","venue":"","topic":"Viral Infections and Outbreaks Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Pandemic; Course (navigation); Mathematics education; Medical education; Coronavirus disease 2019 (COVID-19); Computer science; Psychology; Political science; Engineering; Medicine; Infectious disease (medical specialty); Internal medicine","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":[0.00718697,0.0008776769,0.0006919463,0.001329881,0.007813796,0.00705257,0.001420277,0.00564633,0.01507165],"category_scores_gemma":[0.0181222,0.0005983445,0.0006476711,0.0007463163,0.00193664,0.00429397,0.006037286,0.00715479,0.003183325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004908148,"about_ca_system_score_gemma":0.007488271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008803682,"about_ca_topic_score_gemma":0.01965309,"domain_scores_codex":[0.9953085,0.001381108,0.0001864478,0.0003502004,0.0008074605,0.001966403],"domain_scores_gemma":[0.9701643,0.0027943,0.001148986,0.0002645893,0.00319528,0.0224326],"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":[0.0005777195,0.003508338,0.1840913,0.0008217791,0.0001088654,0.005099857,0.04398771,0.0006240001,0.002185912,0.001506929,0.4736164,0.2838711],"study_design_scores_gemma":[0.0001686091,0.001397554,0.2650344,0.002401643,0.00006693356,0.001132841,0.3391216,0.0008287278,0.001375384,0.0032226,0.3849607,0.0002889902],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.4957663,0.01539053,0.001896961,0.3661922,0.06031585,0.0005462696,0.0009448436,0.0005740338,0.05837303],"genre_scores_gemma":[0.8167735,0.008591066,0.00288825,0.08819918,0.01491485,0.0003752058,0.001013403,0.0002862315,0.06695835],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01507165,"threshold_uncertainty_score":0.05041975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06056264553176986,"score_gpt":0.3631498704452846,"score_spread":0.3025872249135147,"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."}}