{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021919,0.0001677021,0.0003165803,0.00064799,0.00007779603,0.0001806997,0.0009354065,0.00004054959,0.0003789799],"category_scores_gemma":[0.00008016862,0.0001182661,0.00007456947,0.0008662111,0.00004295029,0.0007293902,0.0005603389,0.0002806292,0.00001873424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003558443,"about_ca_system_score_gemma":0.00001039561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002515052,"about_ca_topic_score_gemma":0.001308471,"domain_scores_codex":[0.9987377,0.00008462273,0.0005299629,0.0001794978,0.0002517033,0.0002165241],"domain_scores_gemma":[0.9989542,0.0001170758,0.0004156162,0.000400977,0.00008961181,0.00002250326],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002917156,0.0009311959,0.7338934,0.000262988,0.002628855,0.00006919991,0.02551456,0.0004648235,0.0008017506,0.002745593,0.05194548,0.177825],"study_design_scores_gemma":[0.003155627,0.0001848804,0.854706,0.0007446681,0.003185803,0.0001346376,0.01777999,0.09444913,0.0002204465,0.002201411,0.02232956,0.0009078268],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9717132,0.0002472597,0.01227407,0.001664192,0.0001990245,0.0001515941,0.000002508359,0.00002084092,0.01372729],"genre_scores_gemma":[0.995872,0.0000427736,0.0005905435,0.003038717,0.000189513,0.000001606754,0.00001425883,0.00001596028,0.0002346078],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1769172,"threshold_uncertainty_score":0.4822752,"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."}}