{"id":"W3166307006","doi":"10.22541/au.162224465.58716360/v1","title":"Spatial diffusion of COVID-19: An econometric-based approach.","year":2021,"lang":"en","type":"preprint","venue":"","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Spatial epidemiology; Context (archaeology); Econometrics; Geography; Population; Spatial ecology; Transmission (telecommunications); Computer science; Epidemiology; Cartography; Data science; Environmental health; Medicine; Economics; Ecology; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.002881089,0.000472015,0.0006442186,0.001869941,0.0003333461,0.001146484,0.001022061,0.001139927,0.00389412],"category_scores_gemma":[0.01211921,0.000382336,0.001003077,0.00248869,0.0006703061,0.001456843,0.001195622,0.00118376,0.0004428506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001831815,"about_ca_system_score_gemma":0.001257602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02375815,"about_ca_topic_score_gemma":0.01763634,"domain_scores_codex":[0.9990319,0.000622348,0.00004732481,0.0001251733,0.00009959096,0.00007371598],"domain_scores_gemma":[0.9956605,0.003270791,0.0005752838,0.0001531796,0.0002311941,0.0001090441],"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":[0.00004334242,0.00008369263,0.04235597,0.0001656447,0.0002317503,0.000405351,0.0002551431,0.6328192,0.0004488461,0.2839252,0.006557944,0.03270792],"study_design_scores_gemma":[0.000008332862,0.00001644036,0.003555558,0.00001996808,0.00002372863,0.00006429286,0.0001533944,0.9491211,0.00006203099,0.04411387,0.00284764,0.00001365649],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1222551,0.001923854,0.8601955,0.004287984,0.000212545,0.0002362574,0.002203233,0.0001975394,0.008487856],"genre_scores_gemma":[0.8562819,0.002686113,0.1281936,0.0002735895,0.0001929252,0.0003136961,0.002040369,0.00007363161,0.009944246],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02375815,"threshold_uncertainty_score":0.04723972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3768731367095097,"score_gpt":0.4379800775138986,"score_spread":0.06110694080438889,"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."}}