{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007843195,0.0004096382,0.0005864343,0.00005323187,0.0006730938,0.00008945231,0.0004852573,0.0001160955,0.0002701173],"category_scores_gemma":[0.02296862,0.000268656,0.000324057,0.0005976865,0.0001251858,0.0001159095,0.0004049277,0.0004031912,0.0002292481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002767603,"about_ca_system_score_gemma":0.0001569886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004797048,"about_ca_topic_score_gemma":0.0000652765,"domain_scores_codex":[0.9970911,0.0003869192,0.0007203547,0.0007845606,0.0004162322,0.0006008921],"domain_scores_gemma":[0.9916849,0.006017471,0.0002240269,0.0005529519,0.0001703784,0.001350251],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001418099,0.0001235446,0.008621513,0.0002787381,0.0001469264,0.00002940806,0.003061599,0.4829023,0.0000174538,0.003223905,0.5013136,0.0001392343],"study_design_scores_gemma":[0.0006849801,0.0001525486,0.0002267957,0.00006123272,0.0003430112,0.000004248753,0.0002694573,0.5505198,0.00001708157,0.1357223,0.3113561,0.0006423978],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06398766,0.0003257331,0.7199671,0.2134645,0.0001252132,0.0009752032,0.0001142411,0.0006314067,0.000409015],"genre_scores_gemma":[0.6836984,0.0001733573,0.0007210958,0.314697,0.0003856239,0.0002267344,0.000006290828,0.00004023769,0.00005122113],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.719246,"threshold_uncertainty_score":0.9999766,"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."}}