{"id":"W3211105117","doi":"10.1109/dsaa53316.2021.9564166","title":"Explainable Artificial Intelligence for Data Science on Customer Churn","year":2021,"lang":"en","type":"article","venue":"","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"University of Manitoba","keywords":"Computer science; Artificial intelligence; Big data; Data science; Random forest; Business intelligence; Machine learning; Decision tree; Knowledge management; Data mining","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":["metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002053543,0.0002631842,0.0002639465,0.0003178064,0.0008827127,0.001091632,0.00540738,0.00008437385,0.0002281849],"category_scores_gemma":[0.001698683,0.0002497828,0.0000797848,0.002690599,0.0003808645,0.003585247,0.001992682,0.0002140198,0.001412565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000161259,"about_ca_system_score_gemma":0.001007557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007761856,"about_ca_topic_score_gemma":0.00009258826,"domain_scores_codex":[0.995708,0.00006330815,0.0005714022,0.001752376,0.0008359308,0.001068994],"domain_scores_gemma":[0.9946158,0.0005201013,0.0001176936,0.003617317,0.000841921,0.0002871978],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001291458,0.0001933112,0.000007989682,0.00001623729,0.000006852898,0.00004135693,0.0002879932,0.0005104861,0.0113576,0.8770922,0.00158451,0.1088886],"study_design_scores_gemma":[0.00002911928,0.0001134281,0.00001078049,0.00003003548,0.000005497691,0.00002302351,0.0007567435,0.2917708,0.6187418,0.06453939,0.02363123,0.000348165],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001840642,0.00006830048,0.9613956,0.003673316,0.001240729,0.0003959341,0.00001203448,0.0002958754,0.03107759],"genre_scores_gemma":[0.7784387,0.00005384272,0.2145718,0.002367803,0.0003435276,0.00009855846,0.0000292468,0.00003407164,0.004062428],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8125528,"threshold_uncertainty_score":0.9999955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1734433182678687,"score_gpt":0.3710309403375801,"score_spread":0.1975876220697114,"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."}}