{"id":"W3009351537","doi":"","title":"Racial Disparities in Student Loan Outcomes","year":2020,"lang":"en","type":"article","venue":"Liberty Street Economics","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Debt; Quarter (Canadian coin); Loan; Household debt; Economics; Business; Demographic economics; Monetary economics; Finance; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001497106,0.0001323004,0.0003035475,0.00004263423,0.0002456113,0.000121121,0.0002729264,0.00007785294,0.0001361315],"category_scores_gemma":[0.0001355995,0.000129683,0.00008651346,0.0001068832,0.0001662684,0.0003085352,0.00009513383,0.0001161271,0.00006392899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009808769,"about_ca_system_score_gemma":0.00009179256,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002525613,"about_ca_topic_score_gemma":0.05247605,"domain_scores_codex":[0.9989545,0.00007098045,0.0003124429,0.0002529909,0.0001080813,0.0003010001],"domain_scores_gemma":[0.9994274,0.0002103487,0.00008907796,0.0001080644,0.00002317955,0.0001419356],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001061443,0.00005727375,0.9213375,0.000004345879,0.00003776998,0.000002203398,0.03134244,0.00006349196,1.939356e-7,0.04344847,0.001907387,0.001788342],"study_design_scores_gemma":[0.001253471,0.0001122972,0.7437502,0.00000954905,0.00002785408,8.542694e-8,0.03084356,0.0005489282,0.00001872156,0.00371168,0.219201,0.0005226698],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9285821,0.0001422042,0.0000380206,0.02019127,0.0004939786,0.000239754,0.00003695149,0.00009060273,0.05018516],"genre_scores_gemma":[0.9945806,0.0004329306,0.00009019199,0.002718466,0.0003498167,0.00001848908,0.000007140294,0.00001156291,0.001790792],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2172936,"threshold_uncertainty_score":0.9648138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04397200928930932,"score_gpt":0.2968606808195879,"score_spread":0.2528886715302786,"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."}}