{"id":"W2028340692","doi":"10.5539/ibr.v2n1p96","title":"Applying Fisher Discrimination Approach to Assessing Customers’ Risk in Bank Card Business","year":2009,"lang":"en","type":"article","venue":"International Business Research","topic":"Customer churn and segmentation","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business; Business risks; Actuarial science; Set (abstract data type); Risk analysis (engineering); Marketing; Computer science","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":[0.003563395,0.0004990967,0.000461418,0.002272364,0.0007646297,0.001011032,0.0007015383,0.0009262366,0.001826254],"category_scores_gemma":[0.01033107,0.0002048892,0.0006047238,0.001095456,0.0009349443,0.002066844,0.001273187,0.001075451,0.0001791535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001450947,"about_ca_system_score_gemma":0.001034933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006503974,"about_ca_topic_score_gemma":0.005441375,"domain_scores_codex":[0.9977856,0.0009343014,0.00007530759,0.0002550115,0.0007093708,0.0002404155],"domain_scores_gemma":[0.9959795,0.002849576,0.000344974,0.0001700307,0.0004784432,0.0001773459],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000488106,0.0005704247,0.132273,0.0001994453,0.0001869174,0.001522783,0.002301772,0.2108694,0.006779626,0.2743681,0.004152701,0.3662876],"study_design_scores_gemma":[0.00001539542,0.0001521843,0.02595552,0.00005289172,0.00004427791,0.0003558895,0.0006298029,0.866065,0.002173388,0.1027343,0.001742924,0.00007845329],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.380641,0.0006992976,0.6016501,0.0009181108,0.00009257215,0.0001017974,0.00008094564,0.0001200412,0.01569613],"genre_scores_gemma":[0.9784697,0.0001739895,0.01966152,0.00006757872,0.0000311206,0.0000240866,0.00003825644,0.000007287957,0.001526329],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006503974,"threshold_uncertainty_score":0.0188452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08162346449884117,"score_gpt":0.3603398809347196,"score_spread":0.2787164164358784,"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."}}