{"id":"W4388570126","doi":"10.3390/dynamics3040041","title":"Robust Global Trends during Pandemics: Analysing the Interplay of Biological and Social Processes","year":2023,"lang":"en","type":"article","venue":"Dynamics","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"Natural Sciences and Engineering Research Council of Canada; Agencia Estatal de Investigación; Basque Center for Applied Mathematics; Javna Agencija za Raziskovalno Dejavnost RS; Institute of Physics Belgrade","keywords":"Pandemic; Case fatality rate; Geography; Econometrics; Preparedness; Complex network; Cluster analysis; Population; Computer science; Statistics; Economic geography; Data science; Demography; Coronavirus disease 2019 (COVID-19); Medicine; Infectious disease (medical specialty); Mathematics; Economics; Sociology; Disease","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":[0.001236977,0.0004309195,0.0003738879,0.00194879,0.0003102577,0.0009044459,0.0003690025,0.000557271,0.0007560112],"category_scores_gemma":[0.005426459,0.0001849861,0.000540557,0.001360474,0.0005944949,0.001211844,0.0008046688,0.0005901544,0.0001156464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004426744,"about_ca_system_score_gemma":0.0003233403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004734666,"about_ca_topic_score_gemma":0.002579006,"domain_scores_codex":[0.9996996,0.0001217303,0.00001666245,0.00007815266,0.00004377663,0.00004012957],"domain_scores_gemma":[0.9981614,0.000877987,0.00054418,0.0001635694,0.0001579746,0.00009490609],"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":[0.00020933,0.0001224689,0.2791437,0.0003698175,0.0005721687,0.0008131517,0.002045021,0.5769097,0.01064493,0.04196629,0.002790301,0.08441322],"study_design_scores_gemma":[0.000009445739,0.00006059463,0.1309036,0.00003739419,0.00005270003,0.0001568483,0.0007106659,0.833012,0.000996862,0.03206735,0.001948877,0.00004361168],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8846081,0.0007639085,0.1101539,0.0007334616,0.00004994057,0.00005424229,0.000822501,0.0002012849,0.002612666],"genre_scores_gemma":[0.9911256,0.0001898589,0.008019684,0.00002908215,0.00002903853,0.00002412455,0.0003262818,0.00002872881,0.0002275814],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004734666,"threshold_uncertainty_score":0.009414196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04409732118596954,"score_gpt":0.2476965058337367,"score_spread":0.2035991846477672,"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."}}