{"id":"W2475438435","doi":"10.4018/978-1-930708-26-6.ch013","title":"Understanding Credit Card User's Behaviour","year":2002,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Business Process Modeling and Analysis","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Knowledge extraction; Credit card; Credit card fraud; Process (computing); Task (project management); Data science; Data mining; Database; Artificial intelligence; Machine learning; World Wide Web; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004645627,0.0002413867,0.0002975273,0.001574026,0.0003502202,0.001344407,0.0003461018,0.000801191,0.00479274],"category_scores_gemma":[0.00366185,0.0001106947,0.0001491627,0.0009362913,0.0002308052,0.001127463,0.0003257167,0.0005131735,0.001734602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005177216,"about_ca_system_score_gemma":0.0002559127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01497614,"about_ca_topic_score_gemma":0.01084673,"domain_scores_codex":[0.9997235,0.00007144754,0.00002423311,0.00006086408,0.00007828142,0.00004167769],"domain_scores_gemma":[0.9986337,0.0007876645,0.000175138,0.00006464335,0.0002211964,0.0001176355],"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":[0.000208169,0.0002908988,0.8813248,0.00007740811,0.00003071486,0.0002701932,0.003231282,0.001164786,0.001825252,0.001044736,0.00387532,0.1066564],"study_design_scores_gemma":[0.000006161205,0.0001468707,0.9483652,0.00006947126,0.0000344444,0.0006894813,0.004905742,0.03549961,0.001379896,0.001495165,0.007370521,0.00003737186],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.9772291,0.0006467919,0.005648283,0.001083713,0.00001991427,0.00007518126,0.002378827,0.0002114562,0.01270675],"genre_scores_gemma":[0.9938974,0.0004232001,0.002077254,0.0001084905,0.00001212119,0.00001950712,0.0007009522,0.000009094383,0.002752081],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01497614,"threshold_uncertainty_score":0.02977794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07901022906190953,"score_gpt":0.2373376007302216,"score_spread":0.158327371668312,"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."}}