{"id":"W4366381849","doi":"10.1007/978-3-031-22687-8_12","title":"Robust and Sparse Estimation of Graphical Models Based on Multivariate Winsorization","year":2022,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Estimator; Graphical model; Multivariate statistics; Covariance matrix; Algorithm; Monte Carlo method; Computer science; Estimation of covariance matrices; Context (archaeology); Gaussian; Multivariate normal distribution; Matrix (chemical analysis); Mathematics; Statistics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002997773,0.0002532801,0.0004597883,0.0001667354,0.00007241406,0.000009533393,0.00007660138,0.000188441,0.000587419],"category_scores_gemma":[0.0003167769,0.0002251407,0.00007854558,0.00003186676,0.00007865411,0.00008466854,0.0000550999,0.0002865475,0.000001011434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003641472,"about_ca_system_score_gemma":0.00003220492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008797243,"about_ca_topic_score_gemma":0.000002319497,"domain_scores_codex":[0.9986515,0.00005812875,0.0004409945,0.0003587239,0.0003675397,0.0001231186],"domain_scores_gemma":[0.998065,0.001220634,0.0002672848,0.0002955476,0.00007565016,0.00007591673],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005355137,0.00004030074,7.373561e-8,0.0001161979,0.0000151905,0.000002812079,0.00002284395,0.2045693,0.000006145746,0.7881344,0.00003509011,0.007004055],"study_design_scores_gemma":[0.0002141232,0.00008650155,6.485365e-7,0.00006167353,0.00005217086,5.701793e-7,0.000001525857,0.4925756,0.000008357664,0.5067467,0.000135876,0.0001163151],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000006267687,0.000009155365,0.8533169,0.00005146344,0.00005426728,0.0003661566,0.0001569486,0.00004820015,0.1459906],"genre_scores_gemma":[0.005716696,0.00003297723,0.9750531,0.00007767591,0.0000204736,0.00002319017,0.00009031577,0.00007224311,0.01891336],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2880062,"threshold_uncertainty_score":0.918097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1853991595880927,"score_gpt":0.3662767828175849,"score_spread":0.1808776232294922,"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."}}