{"id":"W2038051688","doi":"10.3138/infor.47.1.15","title":"Dotted Representations of Mean-Variance Efficient Frontiers and their Computation","year":2009,"lang":"en","type":"article","venue":"INFOR Information Systems and Operational Research","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Efficient frontier; Variance (accounting); Portfolio; Computer science; Computation; Mathematical optimization; Variety (cybernetics); Selection (genetic algorithm); Frontier; Mathematics; Algorithm; Economics; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004245677,0.00009792778,0.000208893,0.0007441683,0.0004337776,0.0008287707,0.0001689673,0.00007980529,0.00001193554],"category_scores_gemma":[0.001098894,0.00006901979,0.00003112277,0.000933586,0.0001387687,0.001699222,0.0000478675,0.0001288295,0.00002454148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003199681,"about_ca_system_score_gemma":0.0001652409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001445768,"about_ca_topic_score_gemma":0.000004238233,"domain_scores_codex":[0.9970279,0.0002028648,0.001005641,0.0001668663,0.001420924,0.0001757813],"domain_scores_gemma":[0.9964767,0.0005514958,0.0002613249,0.0002008241,0.002397753,0.0001119723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000168892,0.00005654097,0.006445385,0.00002940703,0.00003362297,6.340115e-7,0.01856015,0.6529337,0.0002576449,0.1655345,0.02584803,0.1301315],"study_design_scores_gemma":[0.0006128091,0.0001216361,0.03895542,0.00003071589,0.000002434552,0.00001639383,0.009080975,0.926484,0.0001547562,0.002275237,0.02214908,0.0001165225],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3785483,0.0007398731,0.5895685,0.002139554,0.0005123012,0.001598077,0.000166565,0.00004372549,0.02668316],"genre_scores_gemma":[0.9974425,0.0001752688,0.001766854,0.00009901736,0.00004419575,0.00002097658,0.0001020538,0.000002523579,0.000346592],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6188943,"threshold_uncertainty_score":0.7991856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08982958862662074,"score_gpt":0.414743734349209,"score_spread":0.3249141457225883,"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."}}