{"id":"W2028470267","doi":"10.1017/s0269888906000737","title":"A survey of Knowledge Discovery and Data Mining process models","year":2006,"lang":"en","type":"article","venue":"The Knowledge Engineering Review","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":388,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Data science; Process (computing); Business process discovery; Interoperability; Knowledge extraction; Process mining; Process modeling; Automation; Knowledge management; Data mining; Work in process; Engineering; Business process; Business process management; World Wide Web; Business process modeling","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001207374,0.0001380946,0.0002739446,0.00003887047,0.00005948018,0.00007155499,0.00167519,0.00002238678,8.151715e-7],"category_scores_gemma":[0.0001160935,0.00009742666,0.00002187266,0.000660972,0.00003584538,0.0006403925,0.0007245654,0.0000871629,0.000007602755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009341035,"about_ca_system_score_gemma":0.00006915636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005455256,"about_ca_topic_score_gemma":0.00003670966,"domain_scores_codex":[0.9990568,0.0000477771,0.0003039674,0.0003359775,0.00008733875,0.0001680981],"domain_scores_gemma":[0.9982213,0.0002800973,0.00008235662,0.001284381,0.00009691175,0.00003492817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001947954,0.0004680764,0.0004860471,0.01265294,0.0001006057,0.000001893417,0.001349314,0.001637953,0.0001364389,0.05433729,0.02044757,0.9083799],"study_design_scores_gemma":[0.00007448395,0.000009716853,0.003792393,0.002019385,0.00002839564,0.000009555325,0.000002724558,0.9863476,0.00002782707,0.0001191453,0.007400224,0.0001685139],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001994503,0.4023069,0.5937769,0.0001362463,0.0001161694,0.0003138922,0.0001059957,0.0001077885,0.001141591],"genre_scores_gemma":[0.9027498,0.02816456,0.06690317,0.00005909103,0.0002994513,0.0002174325,0.0004055205,0.00007908728,0.001121843],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9847097,"threshold_uncertainty_score":0.3972944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06022485778747027,"score_gpt":0.3127235079404043,"score_spread":0.252498650152934,"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."}}