{"id":"W2053068593","doi":"10.3103/s1066530713010043","title":"The bias and risk functions of some Stein-rules in elliptically contoured distributions","year":2013,"lang":"en","type":"article","venue":"Mathematical Methods of Statistics","topic":"Random Matrices and Applications","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Estimator; Subspace topology; Mathematics; Gaussian; Class (philosophy); Applied mathematics; Shrinkage; Matrix (chemical analysis); Random matrix; Distribution (mathematics); Scatter matrix; Random variate; Statistics; Mathematical analysis; Computer science; Artificial intelligence; Random variable; Eigenvalues and eigenvectors; Physics; Estimation of covariance matrices","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001685492,0.0001534801,0.0005000139,0.00006166791,0.0001475997,0.00004771798,0.0001962095,0.00008338974,0.0001115891],"category_scores_gemma":[0.008081677,0.0001001012,0.00007080017,0.0001941871,0.0004656088,0.00007272417,0.00008240871,0.0001981692,0.0000200595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001767387,"about_ca_system_score_gemma":0.00003135922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005654315,"about_ca_topic_score_gemma":0.00001935587,"domain_scores_codex":[0.9979979,0.0003875568,0.0009854106,0.0001650521,0.0002267417,0.0002373872],"domain_scores_gemma":[0.9782016,0.02063056,0.0004242318,0.0004119938,0.0002331438,0.00009844051],"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":[0.00001129607,0.0002216761,0.0001545796,0.0002349146,0.00005689504,2.631216e-7,0.0002081724,0.000003440497,0.0003713854,0.9801618,0.001084873,0.01749072],"study_design_scores_gemma":[0.0004842388,0.00005835589,0.00162765,0.00005166918,0.0001668657,0.000002155569,0.0003890502,0.01121115,0.0004040157,0.9851645,0.000337183,0.0001031302],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07952231,0.0001762468,0.9180353,0.000287015,0.00003011659,0.0006573835,0.0006354987,0.00002027952,0.0006358293],"genre_scores_gemma":[0.03630912,0.0003289532,0.9629011,0.000005681628,0.00002176116,0.000160956,0.000008801503,0.00001888773,0.000244709],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04486581,"threshold_uncertainty_score":0.9675107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06031411722561095,"score_gpt":0.3748316907067962,"score_spread":0.3145175734811852,"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."}}