{"id":"W82815039","doi":"10.1007/0-306-47542-1_19","title":"Knowledge Discovery in Databases and Decision Support","year":2006,"lang":"en","type":"book-chapter","venue":"Kluwer Academic Publishers eBooks","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Computer science; Construct (python library); Decision support system; Data mining; Knowledge extraction; Machine learning; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000608433,0.0004529734,0.0004638043,0.0005706359,0.0001159762,0.0009509363,0.001836442,0.0005018437,0.0000256941],"category_scores_gemma":[0.00004948143,0.0004391021,0.00008879707,0.00008424591,0.0002106008,0.003167464,0.001615172,0.001386617,0.00006916985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001268265,"about_ca_system_score_gemma":0.0003471381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008770179,"about_ca_topic_score_gemma":0.00006219246,"domain_scores_codex":[0.9972166,0.00001627015,0.000694523,0.001193875,0.0004157935,0.0004629695],"domain_scores_gemma":[0.9980507,0.0002859746,0.0002572233,0.001145988,0.00007000952,0.000190134],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003307337,0.00001331879,0.00004360734,0.00002048087,0.00001353757,0.00002159828,0.0001204384,9.349535e-7,0.000008831747,0.1817467,0.4377179,0.3802894],"study_design_scores_gemma":[0.0003667019,0.00002285077,0.0001704008,0.0002654515,0.00001990693,0.00004250699,0.000008304336,0.001404353,0.00001308408,0.04190423,0.9552487,0.0005335655],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00009298623,0.0009584409,0.09892998,0.000224618,0.0005423591,0.0003994525,0.0002965865,0.0001966057,0.8983589],"genre_scores_gemma":[0.0007507626,0.0001180675,0.04291896,0.0005746889,0.0005210492,0.0001029755,0.0007096702,0.0001045105,0.9541993],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5175308,"threshold_uncertainty_score":0.999806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03369944827362448,"score_gpt":0.2842057108848849,"score_spread":0.2505062626112605,"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."}}