{"id":"W3125004740","doi":"10.15353/jcvis.v6i1.3551","title":"Why Can’t Neural Networks Forecast Pandemics Better","year":2021,"lang":"en","type":"article","venue":"Journal of Computational Vision and Imaging Systems","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Universities Space Research Association","keywords":"Pandemic; Computer science; Artificial neural network; Coronavirus disease 2019 (COVID-19); Artificial intelligence; Time series; Econometrics; Machine learning; Economics; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.006538642,0.000975488,0.001032627,0.001250724,0.000490203,0.002761744,0.001192239,0.002836962,0.003151895],"category_scores_gemma":[0.03338894,0.0004495489,0.0006831556,0.0008105885,0.0009468222,0.005373057,0.0007288665,0.003045137,0.001897261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001046475,"about_ca_system_score_gemma":0.000819399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01562838,"about_ca_topic_score_gemma":0.01400977,"domain_scores_codex":[0.9986184,0.0006198453,0.0001087913,0.0003052081,0.0002209269,0.0001267825],"domain_scores_gemma":[0.9891557,0.006936692,0.0007601841,0.0007616889,0.002010143,0.0003755852],"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":[0.0007520837,0.0002148621,0.05597135,0.0005518185,0.0008838256,0.0001972868,0.0003551865,0.5586702,0.002135661,0.02081092,0.05670314,0.3027536],"study_design_scores_gemma":[0.00005493973,0.0001335386,0.005688825,0.000316175,0.00008897499,0.0000719399,0.0002760474,0.9237655,0.001421577,0.06031224,0.00778976,0.00008063404],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2591728,0.02753401,0.4768921,0.1894467,0.008375158,0.0002157366,0.004625913,0.00364459,0.03009302],"genre_scores_gemma":[0.8998923,0.00516081,0.07557871,0.009928576,0.002001032,0.00008976516,0.001658319,0.0003070341,0.005383473],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01562838,"threshold_uncertainty_score":0.03458005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01897117722083076,"score_gpt":0.3094163156293788,"score_spread":0.290445138408548,"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."}}