{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001560752,0.0005828798,0.0006391988,0.001636857,0.0003490649,0.001143381,0.0006167978,0.001012188,0.003328862],"category_scores_gemma":[0.01122427,0.0001600994,0.0006104492,0.001322005,0.0003379435,0.001086753,0.001136728,0.001349378,0.00102013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004743241,"about_ca_system_score_gemma":0.0004556676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01041933,"about_ca_topic_score_gemma":0.005325316,"domain_scores_codex":[0.999341,0.0002189898,0.00004062235,0.0001968159,0.0001027663,0.00009975202],"domain_scores_gemma":[0.9953238,0.002331523,0.0006968364,0.0004276455,0.0006903851,0.0005297325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003930459,0.0004351125,0.7480748,0.00007698678,0.0001967022,0.0003688612,0.0003877828,0.09471142,0.0003810979,0.005931889,0.007733075,0.1413093],"study_design_scores_gemma":[0.0000230279,0.0003245318,0.2038879,0.00009098084,0.0001234691,0.0002958385,0.0005879135,0.7692075,0.0008595334,0.02075898,0.003791123,0.00004934894],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.904171,0.001000979,0.07905874,0.00185322,0.0001651026,0.0001838087,0.003236531,0.0003237225,0.01000693],"genre_scores_gemma":[0.9907112,0.0003272751,0.005527679,0.00007139819,0.00007151779,0.00004566787,0.0009944345,0.00000792501,0.002242944],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01041933,"threshold_uncertainty_score":0.02071738,"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."}}