{"id":"W2803735372","doi":"10.1007/s40595-018-0116-x","title":"A hybrid mobile call fraud detection model using optimized fuzzy C-means clustering and group method of data handling-based network","year":2018,"lang":"en","type":"article","venue":"Vietnam Journal of Computer Science","topic":"Artificial Immune Systems Applications","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Foundation for Climate and Atmospheric Sciences","keywords":"Computer science; Cluster analysis; Data mining; Computational intelligence; Fuzzy logic; Group (periodic table); Artificial intelligence; Group method of data handling; Machine learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.001818512,0.0001215227,0.0002836437,0.0001835256,0.0002461761,0.00009567741,0.0006696574,0.00003189482,0.000001083103],"category_scores_gemma":[0.00001613007,0.0001142933,0.00004333413,0.0004223733,0.0002085407,0.0006903667,0.000241927,0.0001495498,6.408737e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006046338,"about_ca_system_score_gemma":0.00008280764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001516365,"about_ca_topic_score_gemma":0.000009935827,"domain_scores_codex":[0.9986353,0.00004740884,0.0005741235,0.0002116081,0.0002934449,0.0002381352],"domain_scores_gemma":[0.9988301,0.00006473572,0.0002726368,0.0004649612,0.0002655669,0.00010201],"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":[0.00001156305,0.00001153772,0.000009860127,0.00002091281,0.00001240217,9.020766e-7,0.0001571376,0.92858,0.04334198,0.000005513495,0.00002252962,0.02782562],"study_design_scores_gemma":[0.0002697511,0.0001054138,0.00002877509,0.0001368094,0.00002448425,0.0001007263,0.000009254821,0.9923087,0.006687956,0.0001213059,0.00009842506,0.0001083385],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08578811,0.0002077111,0.9133133,0.000009774001,0.0004760038,0.0001556908,0.000003904086,0.00003038021,0.00001518207],"genre_scores_gemma":[0.5138102,0.000005666316,0.4859677,0.00001254999,0.0001924066,0.000001483934,3.160112e-7,0.000009351267,3.588677e-7],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.428022,"threshold_uncertainty_score":0.4660744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0350842635953404,"score_gpt":0.2985424974227257,"score_spread":0.2634582338273853,"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."}}