{"id":"W3005302591","doi":"10.34989/swp-2020-4","title":"A Spatial Model of Bank Branches in Canada","year":2020,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Competitor analysis; Spatial distribution; Competition (biology); Economic geography; Market structure; Distribution (mathematics); Spatial dependence; Geography; Spatial econometrics; Market size; Banking industry; Business; Econometrics; Economics; Industrial organization; Mathematics; Financial system; Statistics; Commerce; Marketing; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0008853378,0.0004894247,0.0007130781,0.002021046,0.002256949,0.003776152,0.002891218,0.001169971,0.0158442],"category_scores_gemma":[0.004167511,0.0005951838,0.001140536,0.004110519,0.001939601,0.00143237,0.001758815,0.001323811,0.0014146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02160635,"about_ca_system_score_gemma":0.01765805,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.982298,"about_ca_topic_score_gemma":0.9675715,"domain_scores_codex":[0.9991737,0.0001244314,0.00002441645,0.0001936374,0.0001412909,0.0003425658],"domain_scores_gemma":[0.9981638,0.0004342369,0.0002954256,0.000117881,0.0006547634,0.0003338311],"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":[0.0002259994,0.0001254144,0.1918542,0.0001474901,0.0001994742,0.0007747263,0.002123166,0.5145268,0.0009323609,0.2268329,0.03709668,0.02516083],"study_design_scores_gemma":[0.0001320724,0.00004925857,0.08623832,0.0001376692,0.0001525806,0.0002233662,0.002287614,0.8356168,0.0002175765,0.03386192,0.04096311,0.0001196005],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8374687,0.00349802,0.03998645,0.01057294,0.0001678718,0.0003030063,0.04063255,0.0006911505,0.06667928],"genre_scores_gemma":[0.9642043,0.001439504,0.004343601,0.0002132934,0.00004130263,0.0001085725,0.004973503,0.00006459842,0.02461142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02160635,"threshold_uncertainty_score":0.1567658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07750229199237729,"score_gpt":0.2657972800434342,"score_spread":0.1882949880510569,"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."}}