{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01058942,0.001077069,0.0006721907,0.002790099,0.001493879,0.003671394,0.002389707,0.002686815,0.005663803],"category_scores_gemma":[0.0536405,0.0006793652,0.001972949,0.002750196,0.002560889,0.006260257,0.005229536,0.005484864,0.0007139641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002435404,"about_ca_system_score_gemma":0.003409911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00399858,"about_ca_topic_score_gemma":0.005491464,"domain_scores_codex":[0.9918677,0.004332979,0.0005870344,0.001184193,0.00179193,0.0002361787],"domain_scores_gemma":[0.9338073,0.05018571,0.00339683,0.009256376,0.002821891,0.0005317247],"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":[0.000124807,0.0002675261,0.007660565,0.0009763489,0.0002920652,0.0007443445,0.002481034,0.1210268,0.002184717,0.5883982,0.01522289,0.2606207],"study_design_scores_gemma":[0.00004748672,0.00005985757,0.001230585,0.0002831338,0.00007473739,0.0002430667,0.0003817561,0.3275652,0.001849574,0.6309127,0.03729454,0.00005734578],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008422781,0.000627204,0.9735264,0.01061954,0.00008633539,0.0001678511,0.0005899314,0.001222974,0.004737044],"genre_scores_gemma":[0.2071926,0.001613813,0.7842982,0.001707746,0.0003497412,0.0004554669,0.001677812,0.0002814038,0.002423104],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01058942,"threshold_uncertainty_score":0.05600286,"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."}}