{"id":"W2737645210","doi":"10.3390/socsci7080123","title":"The Geography of Economic Segregation","year":2018,"lang":"en","type":"article","venue":"Social Sciences","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Inequality; Race (biology); Economic geography; Economic inequality; Demographic economics; Economics; Ethnic group; Geography; Sociology; Gender studies","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.00136214,0.00005437261,0.00008960905,0.00004758305,0.00569979,0.0001112418,0.0003438212,0.0000435367,0.0001052957],"category_scores_gemma":[0.0001407898,0.00003750833,0.00007226197,0.0004297871,0.006010416,0.0002160946,0.00003361294,0.00003470741,0.00004409922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003592554,"about_ca_system_score_gemma":0.0002149931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00242275,"about_ca_topic_score_gemma":0.00721393,"domain_scores_codex":[0.9989704,0.0001366824,0.000160787,0.0001424136,0.0003400378,0.0002496544],"domain_scores_gemma":[0.9993792,0.0002739402,0.0001447892,0.00005373991,0.0001206507,0.00002765282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007461435,0.0000144252,0.1221802,0.000001517741,0.00002575544,6.078415e-8,0.02936029,0.000001096953,0.00002093555,0.8095554,0.01068686,0.02814605],"study_design_scores_gemma":[0.0003145456,0.0002460165,0.2001553,0.00001237115,0.0000335576,1.927863e-7,0.063971,0.0001434914,0.0005365835,0.2964303,0.4378103,0.0003464424],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4071811,0.0004013663,0.00006166297,0.009253108,0.001493191,0.0002015054,0.000006654935,0.00006510883,0.5813364],"genre_scores_gemma":[0.9984072,0.0001415075,0.00006282817,0.00009090128,0.0007315093,0.00000620148,2.888119e-7,0.000002004183,0.0005574956],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5912262,"threshold_uncertainty_score":0.9966947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04625715071557591,"score_gpt":0.3614736780639814,"score_spread":0.3152165273484055,"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."}}