{"id":"W2161480676","doi":"10.3386/w11813","title":"Racial Sorting and Neighborhood Quality","year":2005,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada; National Science Foundation","keywords":"Sorting; Quality (philosophy); Computer science; Geography; Algorithm; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01467228,0.0001925667,0.000586228,0.0005410105,0.0009480285,0.0001431197,0.0003861729,0.0004531603,0.001066325],"category_scores_gemma":[0.008202036,0.000202659,0.0001631429,0.000226502,0.0008452272,0.0002889687,0.0001913,0.0006476246,0.00008561051],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001679012,"about_ca_system_score_gemma":0.00721651,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0120786,"about_ca_topic_score_gemma":0.01010641,"domain_scores_codex":[0.9945691,0.0006167607,0.0009835138,0.0005408784,0.002762208,0.0005275193],"domain_scores_gemma":[0.9933485,0.002829942,0.0005803106,0.0001851823,0.002887101,0.0001689335],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003484471,0.00007382972,0.0139814,0.00007482235,0.0002196771,0.000001148403,0.004335981,0.00001578925,0.000008865047,0.9197018,0.03466462,0.02688728],"study_design_scores_gemma":[0.0009606314,0.0001191605,0.02012331,0.000152657,0.00004321289,0.000003712127,0.00502295,0.0001574907,0.00002909013,0.6089644,0.3637158,0.0007075636],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.002474589,0.002211285,0.000005116952,0.002537138,0.0004966372,0.0004232987,0.00006337848,0.00002846075,0.9917601],"genre_scores_gemma":[0.9587179,0.006036715,0.0001042044,0.00003590749,0.005111137,0.00005854936,0.00009512862,0.0000260409,0.02981439],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9619457,"threshold_uncertainty_score":0.9998468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5988421407198125,"score_gpt":0.617048557711178,"score_spread":0.01820641699136549,"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."}}