{"id":"W2186868313","doi":"","title":"CRM in A Segmented Ebanking/Ecommerce Marketplace â NewApproaches to Data Analysis","year":2011,"lang":"en","type":"article","venue":"The Journal of Internet Banking and Commerce","topic":"Customer churn and segmentation","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Probabilistic logic; Computer science; Customer value; Point (geometry); Market segmentation; Value (mathematics); Data science; Data mining; Marketing; Artificial intelligence; Machine learning; Business","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":[0.01320411,0.0006640108,0.001215368,0.003376081,0.001412041,0.006005505,0.00179704,0.001804271,0.003754065],"category_scores_gemma":[0.03101999,0.0008284627,0.001230148,0.006028568,0.003111088,0.008819083,0.002579016,0.002308681,0.0005446819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002324887,"about_ca_system_score_gemma":0.001949879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009866831,"about_ca_topic_score_gemma":0.01263245,"domain_scores_codex":[0.9933996,0.003636304,0.0003124158,0.001077783,0.00127903,0.0002947823],"domain_scores_gemma":[0.9667097,0.02325821,0.003386396,0.00473243,0.001485361,0.0004279979],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005918559,0.0006156914,0.06449449,0.0005553962,0.0004380459,0.001094069,0.001858719,0.2238543,0.003112482,0.454356,0.007157074,0.241872],"study_design_scores_gemma":[0.00003725524,0.00006249412,0.008372372,0.00008716041,0.00003196212,0.000194086,0.0004235659,0.7450976,0.0006827478,0.2397205,0.005248656,0.00004160195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2132291,0.001293027,0.7670233,0.008381774,0.00008104996,0.0002497395,0.001493262,0.0006089719,0.0076398],"genre_scores_gemma":[0.7588859,0.0009428934,0.2356428,0.000626613,0.0002190813,0.0002616402,0.001116868,0.00008851432,0.002215681],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01320411,"threshold_uncertainty_score":0.06983083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0920942240287273,"score_gpt":0.26453930931249,"score_spread":0.1724450852837627,"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."}}