{"id":"W1958712682","doi":"10.3233/ida-150771","title":"How much effort should be spent to detect fraudulent applications when engaged in classifier-based lending?","year":2015,"lang":"en","type":"article","venue":"Intelligent Data Analysis","topic":"Financial Distress and Bankruptcy Prediction","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Loan; Profit (economics); Computer science; Business; Classifier (UML); Actuarial science; Finance; Artificial intelligence; Economics; Microeconomics","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":[],"consensus_categories":[],"category_scores_codex":[0.00132138,0.0002556,0.0003914438,0.001128674,0.000216349,0.0006009297,0.0009994957,0.0001101134,0.0001749266],"category_scores_gemma":[0.000393715,0.0002397372,0.0001724397,0.002155462,0.0000386778,0.0008376752,0.0004718018,0.0003640808,0.0001668582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001648444,"about_ca_system_score_gemma":0.00003915522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003152841,"about_ca_topic_score_gemma":0.01047622,"domain_scores_codex":[0.9977894,0.00004195773,0.0004548503,0.0007551753,0.0005867633,0.0003718411],"domain_scores_gemma":[0.9981873,0.00006194422,0.000200948,0.001308346,0.0001781906,0.0000632866],"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":[0.0004361713,0.001404521,0.4176462,0.0003776811,0.001612199,0.00008086671,0.0005467091,0.0141769,0.0005116004,0.01039274,0.1203667,0.4324477],"study_design_scores_gemma":[0.0003784474,0.0000264616,0.01879258,0.00004252093,0.001305887,1.954875e-7,0.001373795,0.1130277,0.0007007566,0.00148685,0.8623564,0.0005084625],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07549303,0.0003052427,0.9116724,0.008060186,0.0003875204,0.00136665,0.0004052757,0.0002269358,0.002082741],"genre_scores_gemma":[0.9928274,0.00002021449,0.001335244,0.001448399,0.0005005234,0.00025152,0.003406354,0.00002577696,0.0001845288],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9173344,"threshold_uncertainty_score":0.9776201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1822484865133957,"score_gpt":0.3154700617981531,"score_spread":0.1332215752847574,"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."}}