{"id":"W3209159738","doi":"10.1101/2021.11.04.21265886","title":"The United States COVID-19 Forecast Hub dataset","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Oak Ridge National Laboratory; Natural Sciences and Engineering Research Council of Canada; Quest for Intelligence, Massachusetts Institute of Technology; Plant Sciences Institute, Iowa State University; Advanced Research Projects Agency; National Institute of General Medical Sciences; University of Massachusetts Amherst; Johns Hopkins Bloomberg School of Public Health; University of California, San Diego; Iowa State University; North Carolina State University; Bundesministerium für Bildung und Forschung; University of California, Santa Barbara; Defense Advanced Research Projects Agency; National Institutes of Health; Centers for Disease Control and Prevention; Klaus Tschira Stiftung; San Diego Supercomputer Center; Hôpitaux Universitaires de Genève; Division of Materials Research; Center for Emerging Infectious Diseases, University of Iowa; Defense Threat Reduction Agency; Council of State and Territorial Epidemiologists; Institute for Health Metrics and Evaluation; Wellcome Trust; Indiana University-Purdue University Indianapolis; University of Michigan; National Institute of Diabetes and Digestive and Kidney Diseases; California Institute of Technology; Bill and Melinda Gates Foundation; Los Alamos National Laboratory; Johns Hopkins University; Gordon and Betty Moore Foundation; U.S. Department of Homeland Security; Laboratory Directed Research and Development; National Science Foundation","keywords":"Leverage (statistics); Coronavirus disease 2019 (COVID-19); Download; Government (linguistics); Pandemic; Disease control; Computer science; Scale (ratio); Consensus forecast; Data science; Business; Econometrics; Geography; Infectious disease (medical specialty); Economics; Machine learning; World Wide Web; Environmental health; Medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00153186,0.0009889276,0.0006392539,0.002162236,0.0004959048,0.001135749,0.001440696,0.001292101,0.01603141],"category_scores_gemma":[0.00796984,0.0003465351,0.0009803183,0.002692376,0.0002668956,0.0007129001,0.001144742,0.001302029,0.01104343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008738805,"about_ca_system_score_gemma":0.001404977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02207868,"about_ca_topic_score_gemma":0.02556225,"domain_scores_codex":[0.9991854,0.0002228235,0.00009596889,0.0002262707,0.0001796021,0.00008989198],"domain_scores_gemma":[0.9978289,0.0008136646,0.0002106308,0.0005176606,0.0004615964,0.0001674255],"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":[0.000144879,0.00006299824,0.008630043,0.0002440197,0.00008282028,0.00007531666,0.00003040997,0.006669728,0.0001835037,0.001335624,0.9739826,0.008558046],"study_design_scores_gemma":[0.0009968108,0.0001334425,0.04617423,0.0005669657,0.0001304981,0.0004052836,0.0003011413,0.06236874,0.001684178,0.009875542,0.8772368,0.0001262445],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004976088,0.0003002899,0.0009109782,0.0005439083,0.0001410351,0.00004017171,0.9902397,0.001124782,0.001723081],"genre_scores_gemma":[0.008402484,0.0001131898,0.001477575,0.00009281114,0.00004354972,0.00007042402,0.9892284,0.00007374962,0.0004978734],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02207868,"threshold_uncertainty_score":0.05363041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4000434505669178,"score_gpt":0.4651570160288483,"score_spread":0.06511356546193053,"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."}}