{"id":"W4381885384","doi":"10.1016/j.insmatheco.2023.06.001","title":"A note on portfolios of averages of lognormal variables","year":2023,"lang":"en","type":"article","venue":"Insurance Mathematics and Economics","topic":"Random Matrices and Applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; Wilfrid Laurier University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Log-normal distribution; Mathematics; Homogeneity (statistics); Covariance; Statistics; Random variable; Covariance matrix; Variance (accounting); Variable (mathematics); Block (permutation group theory); Block matrix; Econometrics; Combinatorics; Eigenvalues and eigenvectors; Economics; Mathematical analysis; Physics","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":[0.0003306273,0.0001104577,0.00037374,0.0001036653,0.00004358631,0.00001352715,0.0001260468,0.00005983419,0.00001884413],"category_scores_gemma":[0.00009330213,0.00009813608,0.00006910083,0.0001400858,0.00005611332,0.00005312713,0.00004477106,0.00005437565,0.000009102207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007744923,"about_ca_system_score_gemma":0.0000186421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008785816,"about_ca_topic_score_gemma":0.000003959377,"domain_scores_codex":[0.9991654,0.000006025567,0.0005063212,0.0001269082,0.00005937882,0.0001360157],"domain_scores_gemma":[0.9986954,0.0005878559,0.0003645507,0.0002778184,0.00003879497,0.00003552476],"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":[0.00004241418,0.0003330039,0.001573429,0.001425997,0.00009331189,0.000002133507,0.001777803,0.001737969,0.0007684008,0.9867294,0.001099689,0.004416394],"study_design_scores_gemma":[0.001544823,0.0001192437,0.00253809,0.0002433118,0.00006133642,0.00002358618,0.0004352145,0.03778213,0.006000695,0.9498579,0.001077038,0.000316638],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927355,0.00002642403,0.001641941,0.00008467752,0.00004501789,0.0002097927,0.0001125655,0.00003346974,0.005110589],"genre_scores_gemma":[0.9855899,0.0007743766,0.01339534,0.00001257946,0.0000285349,0.00002318486,0.00000417461,0.00002020863,0.0001517222],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03687156,"threshold_uncertainty_score":0.4001873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02985881988738009,"score_gpt":0.278680675310623,"score_spread":0.2488218554232429,"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."}}