{"id":"W4401880058","doi":"10.1109/compsac61105.2024.00286","title":"Novel Non-linear Adaptive Fuzzy Adjacency Matrices for Financial Volatility Network Models","year":2024,"lang":"en","type":"article","venue":"","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Adjacency matrix; Volatility (finance); Computer science; Adjacency list; Fuzzy logic; Econometrics; Mathematics; Artificial intelligence; Theoretical computer science; Algorithm; Graph","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009413828,0.0006869069,0.0005605101,0.001308198,0.0004548635,0.001034288,0.001270764,0.001006037,0.001802535],"category_scores_gemma":[0.003786583,0.0003988508,0.0007993055,0.001034847,0.000687048,0.001580875,0.0006824892,0.001069423,0.0002481598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009835004,"about_ca_system_score_gemma":0.0006219945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005191801,"about_ca_topic_score_gemma":0.006332255,"domain_scores_codex":[0.9995766,0.0001548567,0.00002013338,0.0001260909,0.00008666682,0.0000356599],"domain_scores_gemma":[0.9987084,0.0007563723,0.0002471056,0.00006570527,0.0001613595,0.00006106086],"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":[0.00002584706,0.00002882173,0.0009949259,0.00004366435,0.00004117116,0.00009966722,0.00008804548,0.8732942,0.001372035,0.103578,0.0005603793,0.0198732],"study_design_scores_gemma":[0.000001103914,0.000004844734,0.0001076048,0.000002067065,0.000003094756,0.000012802,0.000004716749,0.9879833,0.00005990672,0.0116572,0.0001595279,0.000003783117],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03364555,0.0003287903,0.9633679,0.0002243288,0.00002951386,0.00004112615,0.0001299299,0.0001044667,0.002128404],"genre_scores_gemma":[0.8495274,0.000937941,0.143694,0.0001254971,0.00007209033,0.0001868692,0.0003662376,0.00004474235,0.005045261],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005191801,"threshold_uncertainty_score":0.01032317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05691445439756346,"score_gpt":0.2379576754049453,"score_spread":0.1810432210073818,"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."}}