{"id":"W4210293606","doi":"10.1007/s41066-021-00311-0","title":"A perceptual computer for hierarchical portfolio selection based on interval type-2 fuzzy sets","year":2022,"lang":"en","type":"article","venue":"Granular Computing","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Portfolio; Selection (genetic algorithm); Rank (graph theory); Set (abstract data type); Computer science; Perception; Interval (graph theory); Fuzzy set; Fuzzy logic; Artificial intelligence; Machine learning; Data mining; Mathematics; Psychology; Finance","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000918411,0.0004194545,0.0007437284,0.0007581161,0.0004499195,0.001737653,0.001027083,0.0006745922,0.01339581],"category_scores_gemma":[0.00365552,0.0002778026,0.0005323024,0.0006391774,0.0005007593,0.001346706,0.00115292,0.0005378072,0.0009723693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004837239,"about_ca_system_score_gemma":0.0004897411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002037515,"about_ca_topic_score_gemma":0.001850694,"domain_scores_codex":[0.9996754,0.00008674071,0.00002853903,0.00007371142,0.0001087316,0.00002704079],"domain_scores_gemma":[0.9988771,0.0007331388,0.00004494556,0.000132868,0.0001378254,0.00007416754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001666419,0.0002945654,0.001942861,0.000518881,0.0001316101,0.0006255552,0.0007956315,0.1356711,0.0531136,0.07576673,0.01268378,0.7167893],"study_design_scores_gemma":[0.00007407402,0.0001318981,0.0005862138,0.00003957972,0.00004019473,0.0001143411,0.00007726265,0.9640929,0.006641299,0.02253134,0.005643731,0.00002707525],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03091908,0.0001280635,0.9580564,0.0001664739,0.00008828848,0.0001422824,0.0001559057,0.005011645,0.005331837],"genre_scores_gemma":[0.3942511,0.0001640217,0.6018937,0.0001622742,0.00003363215,0.0002082484,0.0001853593,0.0002758858,0.002825716],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01339581,"threshold_uncertainty_score":0.04481345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1215927492058651,"score_gpt":0.3953482125052738,"score_spread":0.2737554632994088,"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."}}