{"id":"W3141059875","doi":"10.1007/s10618-005-1355-x","title":"Mining Customer Value: From Association Rules to Direct Marketing","year":2005,"lang":"en","type":"article","venue":"Data Mining and Knowledge Discovery","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":117,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Association rule learning; Profit (economics); Computer science; Data mining; Liberian dollar; Direct marketing; Customer lifetime value; Customer value; Marketing; Artificial intelligence; Machine learning; Customer retention; Business; Economics; Finance","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001721778,0.0002407202,0.0003013031,0.000244125,0.0003174103,0.001019262,0.0004194648,0.00008908775,0.000137113],"category_scores_gemma":[0.001156931,0.0002397806,0.00004765089,0.0003256862,0.00002113547,0.00287422,0.001073962,0.0001151654,0.0003246163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005745494,"about_ca_system_score_gemma":0.00003317615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005485662,"about_ca_topic_score_gemma":0.0008039051,"domain_scores_codex":[0.9983701,0.00005840522,0.0003314464,0.0006255175,0.0002236742,0.000390821],"domain_scores_gemma":[0.998475,0.0007219609,0.000190451,0.0005095982,0.00007115172,0.00003190919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000922464,0.00008247417,0.4113661,0.00006944741,0.00007492074,0.000005011433,0.0006713798,0.000003914129,0.0004219501,0.00005335912,0.0728948,0.5142643],"study_design_scores_gemma":[0.0006684645,0.000004671067,0.3125533,0.0004685353,0.0004074737,0.000001078877,0.001393433,0.006928707,0.000042772,0.000009137526,0.6768397,0.0006826952],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9281328,0.001013369,0.00004970183,0.0003620448,0.000577673,0.0001183757,0.0001922048,0.0001240583,0.06942983],"genre_scores_gemma":[0.9899226,0.0000459981,0.002027384,0.0005631355,0.002425049,0.00001361992,0.001166923,0.00004517689,0.003790069],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.603945,"threshold_uncertainty_score":0.9828768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03081130680570864,"score_gpt":0.2724500237614445,"score_spread":0.2416387169557359,"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."}}