{"id":"W2588272059","doi":"","title":"FUZZY PORTFOLIO OPTIMIZATION MODEL WITH ESTIMATION OF RESULTS","year":2016,"lang":"en","type":"article","venue":"The Journal of Internet Banking and Commerce","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Fuzzy logic; Variance (accounting); Portfolio; Reliability (semiconductor); Portfolio optimization; Mathematical optimization; Fuzzy number; Modern portfolio theory; Econometrics; Fuzzy set; Artificial intelligence; Mathematics; Economics; Finance","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":[],"consensus_categories":[],"category_scores_codex":[0.00282945,0.001036433,0.001387025,0.0009398597,0.0004847781,0.00240054,0.001840944,0.002211377,0.0025799],"category_scores_gemma":[0.004937221,0.0004768085,0.001274794,0.0009759305,0.0008387511,0.002207328,0.001193568,0.0014259,0.0003363624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00138896,"about_ca_system_score_gemma":0.001279306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00369385,"about_ca_topic_score_gemma":0.001448469,"domain_scores_codex":[0.9983197,0.0006693183,0.0000827019,0.0003763797,0.0004000297,0.00015187],"domain_scores_gemma":[0.9989834,0.0005925882,0.0001379174,0.00005701673,0.0001860351,0.00004298848],"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":[0.00004816061,0.00003601114,0.0007026122,0.00007508129,0.00005942127,0.0001020337,0.00007021035,0.8584225,0.0004944738,0.1210794,0.0007186297,0.01819137],"study_design_scores_gemma":[0.000007635351,0.00001627912,0.00008542454,0.00000784689,0.00001261898,0.00001714546,0.000006729677,0.9828912,0.0001311811,0.01640922,0.0004065792,0.000008135519],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00863375,0.0004325067,0.9868463,0.0004382669,0.00004108893,0.00003318312,0.00004887926,0.00007351809,0.003452553],"genre_scores_gemma":[0.8155885,0.001253201,0.1700563,0.0002156973,0.0001570017,0.0003722826,0.0001961859,0.00004624455,0.01211454],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00369385,"threshold_uncertainty_score":0.01496375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04340148594208759,"score_gpt":0.3151345873256494,"score_spread":0.2717331013835618,"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."}}