{"id":"W2985552643","doi":"","title":"Advanced Data Mining and Applications: 5th International Conference, ADMA 2009, Beijing, China, August 17-19, 2009: Proceedings","year":2009,"lang":"en","type":"article","venue":"Advanced Data Mining and Applications","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Beijing; China; Computer science; Chinese academy of sciences; Data science; Political science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007063755,0.001009045,0.002262232,0.001928796,0.001000837,0.00331505,0.001958156,0.001364005,0.0161078],"category_scores_gemma":[0.005192222,0.0007903938,0.001012863,0.002330048,0.001130814,0.003567621,0.001932522,0.002898073,0.009901023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009073962,"about_ca_system_score_gemma":0.002935968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003649991,"about_ca_topic_score_gemma":0.005018313,"domain_scores_codex":[0.9983374,0.0002805958,0.0001889293,0.0002896826,0.0007996266,0.0001038384],"domain_scores_gemma":[0.9958598,0.0006231714,0.0001024677,0.0005743968,0.002349374,0.0004908576],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003307842,0.0003642924,0.002280901,0.0004950869,0.0001258818,0.0001661241,0.0001656475,0.001526823,0.006618078,0.003893349,0.3189305,0.6651025],"study_design_scores_gemma":[0.0001274006,0.0006618694,0.01534936,0.0005661792,0.0003752978,0.002019702,0.0005253316,0.09121768,0.02240505,0.0149898,0.851628,0.0001343336],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.03652386,0.1131619,0.7535725,0.01878999,0.02811261,0.001171445,0.004560431,0.01221656,0.03189071],"genre_scores_gemma":[0.1067114,0.0864547,0.5258188,0.003706566,0.006458533,0.0007556247,0.01976917,0.001755641,0.2485696],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.0161078,"threshold_uncertainty_score":0.05388594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04427514903601441,"score_gpt":0.3306492694076625,"score_spread":0.2863741203716481,"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."}}