{"id":"W2047803154","doi":"10.1016/j.crma.2010.12.014","title":"Sharp bounds on the rate of convergence of the empirical covariance matrix","year":2011,"lang":"en","type":"article","venue":"Comptes Rendus Mathématique","topic":"Random Matrices and Applications","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Rate of convergence; Mathematics; Convergence (economics); Matrix (chemical analysis); Covariance matrix; Covariance; Applied mathematics; Econometrics; Statistics; Economics; Computer science; Chemistry; Key (lock)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005662605,0.0001542625,0.0003169668,0.00003365428,0.0001253953,0.00001494774,0.0007556309,0.00008365976,0.001074408],"category_scores_gemma":[0.0002846922,0.00008286252,0.0001565432,0.0003339341,0.0002119647,0.0000435501,0.0001260975,0.0002124602,0.00006817474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001685761,"about_ca_system_score_gemma":0.00006142459,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004224703,"about_ca_topic_score_gemma":0.000006378556,"domain_scores_codex":[0.9987514,0.000193186,0.0005317635,0.0001726452,0.0001849747,0.0001660193],"domain_scores_gemma":[0.9973422,0.001102204,0.0005204238,0.0008787094,0.0001187348,0.00003777421],"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":[0.00005323985,0.0002894021,0.001436451,0.0001907155,0.00005907883,7.804441e-7,0.002259016,0.00001334905,0.002130761,0.9524375,0.04106001,0.00006973284],"study_design_scores_gemma":[0.001302962,0.0001893852,0.02899001,0.0005085749,0.0001870459,0.00002441107,0.0006773258,0.005439662,0.1015822,0.8502879,0.01033587,0.0004746052],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9718764,0.0002253936,0.00748827,0.001959194,0.0002057619,0.0009262863,0.0000750877,0.00006672485,0.01717688],"genre_scores_gemma":[0.9943664,0.00006914544,0.004595367,0.0001663418,0.0000286289,0.00008146963,0.000001386105,0.00002018444,0.0006710469],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1021495,"threshold_uncertainty_score":0.9998388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.259199147804874,"score_gpt":0.3602732956523986,"score_spread":0.1010741478475247,"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."}}