{"id":"W4280578743","doi":"10.1016/j.sigpro.2022.108620","title":"Censoring outliers in elliptically symmetric multivariate distribution","year":2022,"lang":"en","type":"article","venue":"Signal Processing","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Outlier; Censoring (clinical trials); Mathematics; Mathematical optimization; Covariance; Gaussian; Algorithm; Computational complexity theory; Stationary point; Computer science; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007702488,0.0001250221,0.0002151847,0.0001007387,0.0002909445,0.00003321003,0.000127269,0.00003334058,0.00007752412],"category_scores_gemma":[0.0006937164,0.0001238273,0.00003780891,0.0005843711,0.00003629227,0.000123694,0.0001105962,0.0003847569,0.000002558237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002288081,"about_ca_system_score_gemma":0.00005601862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000889379,"about_ca_topic_score_gemma":8.670679e-7,"domain_scores_codex":[0.9985478,0.000164476,0.0003356767,0.0002811552,0.0003230585,0.0003478438],"domain_scores_gemma":[0.9990924,0.0005769376,0.0001101349,0.00009305685,0.00005026048,0.00007721486],"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":[0.0001686694,0.0004259943,0.0002515328,0.0003301138,0.00001589103,0.00009757468,0.0009986642,0.008439154,0.005037976,0.3921466,0.00006049228,0.5920274],"study_design_scores_gemma":[0.0005892959,0.00008208133,0.0002206404,0.00005872291,0.00002418205,0.000009373131,0.0004953806,0.2260828,0.0004376672,0.7711486,0.0005949187,0.000256308],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01382341,0.0001020363,0.9845193,0.00007147715,0.00005494668,0.000164579,0.00004119382,0.00006763815,0.001155419],"genre_scores_gemma":[0.7630073,0.000001311137,0.2367478,0.00003408262,0.00003126001,0.00003942066,0.00001006055,0.00001942597,0.0001093446],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7491839,"threshold_uncertainty_score":0.504953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09880669015401773,"score_gpt":0.3981913301496969,"score_spread":0.2993846399956792,"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."}}