{"id":"W7020245921","doi":"","title":"KDD 2002 proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining ; July 23 - 26, 2002, Edmonton, Alberta, Canada","year":2002,"lang":"en","type":"article","venue":"","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Knowledge extraction; Association rule learning; Web mining; Software mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007051578,0.002048807,0.005961758,0.003623169,0.003266111,0.01330988,0.004559941,0.002366702,0.02683273],"category_scores_gemma":[0.0113959,0.001570545,0.001858472,0.003816694,0.0017815,0.00419801,0.002987964,0.004826193,0.03026351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003924753,"about_ca_system_score_gemma":0.0154546,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1363983,"about_ca_topic_score_gemma":0.2350425,"domain_scores_codex":[0.9962479,0.0005971356,0.0003082042,0.000380278,0.00219324,0.0002731129],"domain_scores_gemma":[0.9872642,0.001353822,0.000224487,0.001547983,0.007798975,0.001810523],"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":[0.0002669792,0.0003867068,0.001286229,0.0003376893,0.0001923657,0.0001545593,0.0001628952,0.002269176,0.0007546745,0.002946091,0.88009,0.1111526],"study_design_scores_gemma":[0.000250863,0.0001293163,0.005747563,0.000279589,0.0003933154,0.0004799863,0.0005403709,0.03288395,0.006259422,0.0130339,0.9398541,0.0001475406],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.04059118,0.05310766,0.4861705,0.05802359,0.1166454,0.002852918,0.07767396,0.04125614,0.1236785],"genre_scores_gemma":[0.07320253,0.04219769,0.3096784,0.006871148,0.004609108,0.000743746,0.1745759,0.00477813,0.3833433],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8636017,"threshold_uncertainty_score":0.2712086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05070213935716859,"score_gpt":0.2677372799557711,"score_spread":0.2170351405986025,"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."}}