{"id":"W2071339967","doi":"10.1504/ijbidm.2012.051713","title":"Multi-level relationship outlier detection","year":2012,"lang":"en","type":"article","venue":"International Journal of Business Intelligence and Data Mining","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Anomaly detection; Data mining; Outlier; Data science; Artificial intelligence","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":[0.003020152,0.0009544138,0.002004382,0.004720703,0.0009958181,0.00234811,0.003074692,0.001677497,0.0009732336],"category_scores_gemma":[0.0170025,0.0003671518,0.001128478,0.006046499,0.0007696691,0.003553742,0.002621774,0.002091421,0.0008948458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007352845,"about_ca_system_score_gemma":0.0009960732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001861207,"about_ca_topic_score_gemma":0.002073507,"domain_scores_codex":[0.991869,0.001223677,0.0005701744,0.001602102,0.004204077,0.0005310443],"domain_scores_gemma":[0.9827061,0.005937704,0.004859521,0.002935609,0.003034486,0.0005266327],"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":[0.0004049399,0.0008089794,0.1855957,0.0005893707,0.0004948723,0.001704422,0.000792397,0.09716713,0.02529841,0.0179584,0.01081698,0.6583684],"study_design_scores_gemma":[0.00002253471,0.0003084081,0.02216433,0.00005606126,0.0001007592,0.001620152,0.0004894658,0.9237812,0.01890108,0.02380739,0.008665029,0.00008361504],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1008318,0.0008115717,0.8916643,0.0007555715,0.000095885,0.0001672968,0.0008176184,0.003276644,0.001579411],"genre_scores_gemma":[0.7372157,0.000580576,0.2578631,0.0002058115,0.0001391178,0.0001293316,0.001892312,0.000154797,0.001819249],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004720703,"threshold_uncertainty_score":0.01597226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2305228817311848,"score_gpt":0.3778292560200253,"score_spread":0.1473063742888405,"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."}}