{"id":"W2936364519","doi":"10.3390/risks7020042","title":"Defining Geographical Rating Territories in Auto Insurance Regulation by Spatially Constrained Clustering","year":2019,"lang":"en","type":"article","venue":"Risks","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Toronto Metropolitan University","funders":"","keywords":"Cluster analysis; Statistic; Computer science; Econometrics; Entropy (arrow of time); Homogeneity (statistics); Actuarial science; Data mining; Statistics; Business; Economics; Mathematics; Machine learning","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":[0.003191527,0.0006354231,0.001118962,0.002291272,0.0008535779,0.002056301,0.001540268,0.001038173,0.001474893],"category_scores_gemma":[0.01327112,0.0005598523,0.001078308,0.002076331,0.00131325,0.001743897,0.002353386,0.0007401634,0.0003057046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001615322,"about_ca_system_score_gemma":0.001868172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009457926,"about_ca_topic_score_gemma":0.009985941,"domain_scores_codex":[0.9947771,0.002943043,0.0003013225,0.0008075336,0.0009325233,0.0002383998],"domain_scores_gemma":[0.9920218,0.004380281,0.001160537,0.000969127,0.001240758,0.0002274171],"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":[0.0001033338,0.000063555,0.01278978,0.0001956952,0.00007887778,0.0001835164,0.0006063758,0.837144,0.003492658,0.06144634,0.001356209,0.08253969],"study_design_scores_gemma":[0.00001084096,0.00006822781,0.004642231,0.00003954889,0.00002700675,0.000135869,0.0003937222,0.9688071,0.002220606,0.0196334,0.003974867,0.00004659984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05588609,0.0001789203,0.9410174,0.0001342178,0.00001111238,0.0001707464,0.0002114044,0.0001342531,0.002255803],"genre_scores_gemma":[0.6099997,0.0002221108,0.3873772,0.00004186948,0.00001588568,0.0003804482,0.0005271726,0.0000820751,0.001353532],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009457926,"threshold_uncertainty_score":0.01880574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01185182908226527,"score_gpt":0.2796724173299001,"score_spread":0.2678205882476348,"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."}}