{"id":"W2356803596","doi":"","title":"Application of Data Warehouse in Commercial Banks","year":2008,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Data warehouse; Computer science; Dimensional modeling; Data transformation; Process (computing); Data flow diagram; Competition (biology); Credit card; Architecture; Warehouse; Database; Data science; World Wide Web; Business; Marketing","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":[0.003433449,0.000433473,0.0004219084,0.001636397,0.0008903412,0.003231177,0.001098606,0.001005193,0.001383724],"category_scores_gemma":[0.005101841,0.0006324095,0.0006294382,0.004168142,0.0004871742,0.002789547,0.001252993,0.0009149209,0.0007317223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009526917,"about_ca_system_score_gemma":0.001273629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003394568,"about_ca_topic_score_gemma":0.001844952,"domain_scores_codex":[0.9976177,0.001065816,0.000328565,0.0002992469,0.0006034187,0.00008528844],"domain_scores_gemma":[0.9971563,0.001102236,0.0001124248,0.000706711,0.0007832723,0.0001390896],"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":[0.0009291096,0.0007939536,0.02464029,0.001531973,0.0003184065,0.003444941,0.005212069,0.0672479,0.03566606,0.1089522,0.03749683,0.7137663],"study_design_scores_gemma":[0.0002182245,0.0003181786,0.007924607,0.0004925691,0.0002137408,0.002096382,0.003348513,0.5820784,0.08915775,0.05721286,0.2567132,0.0002256011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1168069,0.001951065,0.8427617,0.004229645,0.0003118505,0.000599428,0.002270903,0.008720544,0.022348],"genre_scores_gemma":[0.4002671,0.003048437,0.5900956,0.0004718821,0.00009276583,0.0002595739,0.002357519,0.0003017888,0.003105336],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003433449,"threshold_uncertainty_score":0.01815802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04650231801150504,"score_gpt":0.2897995692173535,"score_spread":0.2432972512058485,"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."}}