{"id":"W3012864042","doi":"10.1016/j.idm.2020.03.001","title":"Why is it difficult to accurately predict the COVID-19 epidemic?","year":2020,"lang":"en","type":"article","venue":"Infectious Disease Modelling","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":690,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Akaike information criterion; Coronavirus disease 2019 (COVID-19); Quarantine; Model selection; Outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Range (aeronautics); Geography; Epidemic model; Econometrics; Statistics; Mathematics; Demography; Virology; Engineering; Population; Biology; Medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.009191119,0.001054349,0.001310784,0.001033598,0.0006176443,0.00272021,0.002527465,0.00274468,0.001250077],"category_scores_gemma":[0.04145399,0.0009110763,0.0008723693,0.001103124,0.001076819,0.004463019,0.001418768,0.002799259,0.000578316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001872131,"about_ca_system_score_gemma":0.002384142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06965153,"about_ca_topic_score_gemma":0.03900835,"domain_scores_codex":[0.9968911,0.001797706,0.0001589321,0.0005762741,0.0002821268,0.0002939474],"domain_scores_gemma":[0.9869505,0.008834749,0.001407624,0.0009347284,0.001524796,0.0003476781],"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":[0.0001372652,0.0001170075,0.09323898,0.0002556228,0.000311809,0.0003875672,0.0006312376,0.8577709,0.0008077857,0.01134773,0.005655753,0.0293384],"study_design_scores_gemma":[0.00004504119,0.0001168693,0.0221942,0.0002159848,0.00005215978,0.0001490367,0.0008043574,0.9310538,0.0005204474,0.04112059,0.003649092,0.00007846517],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7095005,0.004103463,0.2226456,0.04642904,0.0007144182,0.0002893556,0.004659472,0.0009561034,0.01070203],"genre_scores_gemma":[0.9669331,0.001116788,0.02807714,0.001078872,0.000143955,0.0001024762,0.001448748,0.00006909264,0.001029787],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06965153,"threshold_uncertainty_score":0.1384922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4522978377807975,"score_gpt":0.4371180193562929,"score_spread":0.01517981842450467,"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."}}