{"id":"W3053629049","doi":"10.6339/jds.202007_18(3).0018","title":"Data Visualization and Descriptive Analysis for Understanding Epidemiological Characteristics of COVID-19: A Case Study of a Dataset from January 22, 2020 to March 29, 2020","year":2021,"lang":"en","type":"article","venue":"Journal of Data Science","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Case fatality rate; Epidemiology; Coronavirus disease 2019 (COVID-19); Coronavirus; Incubation period; Medicine; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Nonparametric statistics; Disease; Internal medicine; Pathology; Statistics; Psychology; Incubation; Infectious disease (medical specialty); Outbreak","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":[0.002916066,0.000466183,0.0003911013,0.00516503,0.0004967499,0.001128698,0.0005815027,0.0007286182,0.0009666566],"category_scores_gemma":[0.01023502,0.0001340118,0.0007893953,0.003753086,0.0003175457,0.0008277163,0.0008241082,0.0007047968,0.0002944873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008344476,"about_ca_system_score_gemma":0.0009319613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01178919,"about_ca_topic_score_gemma":0.01850767,"domain_scores_codex":[0.9988287,0.0004012554,0.0002088791,0.0002004918,0.0002528817,0.0001078205],"domain_scores_gemma":[0.9892916,0.006818557,0.001361088,0.0009259353,0.001213797,0.0003890709],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009413682,0.0005844994,0.8462569,0.000643437,0.0003733301,0.002731547,0.001682336,0.01836485,0.003846403,0.004238222,0.03728856,0.08304857],"study_design_scores_gemma":[0.00009494071,0.0003504857,0.7524094,0.0003116393,0.0001709746,0.002976158,0.006671122,0.1643013,0.005102398,0.007431256,0.06005315,0.000127171],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8597265,0.001843299,0.01727661,0.003889458,0.0001596635,0.0001944561,0.1131064,0.001081824,0.002721892],"genre_scores_gemma":[0.8701321,0.0004990499,0.03954434,0.0001400584,0.00008685103,0.0001973348,0.08856386,0.00007156636,0.0007648261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01178919,"threshold_uncertainty_score":0.02344108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6960204092600549,"score_gpt":0.5511004728700827,"score_spread":0.1449199363899722,"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."}}