{"id":"W2485902335","doi":"","title":"Credit Risk Prediction to Individuals","year":2016,"lang":"en","type":"article","venue":"The Journal of Internet Banking and Commerce","topic":"Economic, Social, and Public Health Issues in Russia and Globally","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Loan; Default; Reliability (semiconductor); Credit risk; Computer science; Investment (military); Financial risk; Actuarial science; Econometrics; Predictive modelling; Business; Finance; Economics; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008902739,0.00009140251,0.0002445047,0.0001335388,0.0001616145,0.0001691626,0.0008131363,0.0000628395,0.0004477266],"category_scores_gemma":[0.001639818,0.00004033921,0.00007508548,0.0001383785,0.00009093825,0.0002516071,0.0001428079,0.0001978681,0.00008731488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004208682,"about_ca_system_score_gemma":0.00005674808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001046417,"about_ca_topic_score_gemma":0.00002835865,"domain_scores_codex":[0.997898,0.0005391602,0.0007932239,0.0001175099,0.0004606007,0.0001915433],"domain_scores_gemma":[0.9967222,0.002070034,0.0006069362,0.0002310184,0.0002010336,0.0001687822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001494322,0.00003665181,0.1870338,0.000003242613,0.00008347474,0.000002280345,0.01067624,0.0000185607,0.00003288198,0.004787905,0.3920302,0.4051453],"study_design_scores_gemma":[0.0005860269,0.000552175,0.2108498,0.0001757653,0.00003545819,0.0001258527,0.001521367,0.00006454738,0.00006522141,0.04575125,0.7401665,0.000106035],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.958748,0.0004083392,0.008668409,0.02248394,0.001279739,0.00006745604,0.00002900482,0.000009479943,0.008305654],"genre_scores_gemma":[0.9946911,0.0004231259,0.0001886033,0.002060353,0.0006511188,8.19032e-7,1.455137e-7,0.000005290151,0.001979439],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4050393,"threshold_uncertainty_score":0.4902292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06375928823264607,"score_gpt":0.3609385828059519,"score_spread":0.2971792945733058,"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."}}