{"id":"W2313932402","doi":"10.1515/ijnsns.2004.5.2.157","title":"A Probabilistic Method for Detecting Multivariate Extreme Outliers","year":2004,"lang":"en","type":"article","venue":"International Journal of Nonlinear Sciences and Numerical Simulation","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Outlier; Multivariate statistics; Probabilistic logic; Computer science; Multivariate analysis; Statistics; Artificial intelligence; Data mining; Econometrics; Machine learning; Mathematics","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":[0.006019189,0.001373638,0.001572834,0.00529793,0.00160418,0.002105491,0.002768765,0.002430153,0.004372507],"category_scores_gemma":[0.0335604,0.001057478,0.002324442,0.003982977,0.002235836,0.002593031,0.003854648,0.003638206,0.00168685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006543267,"about_ca_system_score_gemma":0.001741185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001357357,"about_ca_topic_score_gemma":0.001184864,"domain_scores_codex":[0.9919287,0.002434016,0.0003992959,0.001144787,0.003763669,0.000329448],"domain_scores_gemma":[0.9843887,0.007551918,0.002074155,0.001674366,0.003775089,0.0005358521],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007560685,0.0001750032,0.006606727,0.0005863767,0.0006022577,0.0007045848,0.0002725947,0.2921072,0.03000209,0.1339928,0.01362273,0.5205716],"study_design_scores_gemma":[0.00005662438,0.0001472581,0.001630089,0.00005150204,0.00008136231,0.0007450712,0.00003348695,0.911893,0.007566683,0.06853049,0.009117945,0.0001464191],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009515568,0.00007523389,0.9984112,0.00005941057,0.00004149065,0.0000192103,0.00003873817,0.0001816057,0.000221575],"genre_scores_gemma":[0.09258771,0.0003496036,0.9027435,0.0001972995,0.0004386952,0.0003061251,0.0004745901,0.0002823303,0.002620165],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006019189,"threshold_uncertainty_score":0.03183287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1894897570846573,"score_gpt":0.4909322778687356,"score_spread":0.3014425207840783,"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."}}