{"id":"W4318992068","doi":"10.5267/j.ac.2022.12.003","title":"Bibliometric analysis of risk measures for portfolio optimization","year":2023,"lang":"en","type":"article","venue":"Accounting","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Portfolio optimization; Portfolio; Modern portfolio theory; Actuarial science; Computer science; Risk measure; Variety (cybernetics); Risk analysis (engineering); Econometrics; Economics; Business; Financial 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01139824,0.001407585,0.002204902,0.1738048,0.001483249,0.007247916,0.001185346,0.001010089,0.00794042],"category_scores_gemma":[0.09326694,0.0004260198,0.002488442,0.2016665,0.001179546,0.006029411,0.002605505,0.0007963151,0.001800051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003244302,"about_ca_system_score_gemma":0.00571968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004078252,"about_ca_topic_score_gemma":0.003873873,"domain_scores_codex":[0.9766236,0.004363313,0.004448188,0.00143234,0.01262338,0.0005092589],"domain_scores_gemma":[0.8975076,0.06387999,0.01788819,0.00319304,0.01673118,0.0007999698],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002493215,0.0001231401,0.0894101,0.04848253,0.002861267,0.0005465145,0.002827847,0.004926898,0.001480036,0.03197476,0.05058478,0.7665328],"study_design_scores_gemma":[0.0001224262,0.0003537774,0.3511661,0.03635413,0.007366702,0.003030656,0.007668758,0.01728529,0.00558342,0.06332105,0.5071944,0.000553367],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1806642,0.4801503,0.05497514,0.009607488,0.001972643,0.001881013,0.09490778,0.002108858,0.1737326],"genre_scores_gemma":[0.6688578,0.2367756,0.04810091,0.0006504196,0.001950717,0.002188732,0.03441776,0.0003313695,0.006726776],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8261952,"threshold_uncertainty_score":0.06028038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02714560616828989,"score_gpt":0.29847913722563,"score_spread":0.2713335310573401,"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."}}