{"id":"W581782849","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":"book","venue":"Association for Computing Machinery eBooks","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":100,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Knowledge extraction; Library science; Data science; Computer science; Data 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006191179,0.0004082427,0.000474303,0.0001209635,0.0004125303,0.0005396809,0.004260379,0.0002245436,0.000007091453],"category_scores_gemma":[0.0005211383,0.0003489197,0.0001073873,0.0000992291,0.00006616118,0.0003176043,0.002301766,0.0004499191,0.000009882399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005834778,"about_ca_system_score_gemma":0.0009100815,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.007891564,"about_ca_topic_score_gemma":0.02823061,"domain_scores_codex":[0.9972509,0.00003351601,0.0006837159,0.0009748547,0.0006740251,0.00038306],"domain_scores_gemma":[0.9957987,0.001052064,0.00149845,0.001068999,0.000485142,0.00009662351],"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":[0.000004464081,0.00006511415,0.0003041929,0.00007233255,0.0002235789,5.28997e-7,0.0006698079,0.000008523782,0.0000118624,0.03735219,0.9297746,0.03151285],"study_design_scores_gemma":[0.0007370426,0.00008143007,0.001356737,0.0006232959,0.0001301367,0.000009265483,0.00002886902,0.2974429,0.0000401422,0.002155722,0.6967013,0.0006931279],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0005183038,0.0002017415,0.004191962,0.002369213,0.002452773,0.001278557,0.002596856,0.0001772761,0.9862133],"genre_scores_gemma":[0.008375054,0.00001676083,0.009105779,0.0003398644,0.0006665995,0.00003291266,0.0003482473,0.00006552195,0.9810492],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2974344,"threshold_uncertainty_score":0.9998963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02990121733667554,"score_gpt":0.2639706669744599,"score_spread":0.2340694496377844,"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."}}