{"id":"W4388706525","doi":"10.1016/j.inffus.2023.102145","title":"A dynamic multiple classifier system using graph neural network for high dimensional overlapped data","year":2023,"lang":"en","type":"article","venue":"Information Fusion","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec; Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Computer science; Classifier (UML); Artificial intelligence; Curse of dimensionality; Machine learning; Artificial neural network; Locality; Graph; Pattern recognition (psychology); Data mining; Theoretical computer science","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":[0.002117425,0.001669892,0.001675048,0.002429676,0.001164987,0.001477044,0.003380434,0.001831445,0.002460479],"category_scores_gemma":[0.003617431,0.0006000103,0.001146855,0.001885639,0.0005449927,0.003368282,0.00204411,0.002549862,0.001769155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00160224,"about_ca_system_score_gemma":0.00125769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0129243,"about_ca_topic_score_gemma":0.01748642,"domain_scores_codex":[0.9983897,0.0002574422,0.00007282853,0.000720401,0.0004099757,0.0001496649],"domain_scores_gemma":[0.9985863,0.0004599238,0.0001377878,0.0002767329,0.0004292153,0.0001100626],"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":[0.000465275,0.0005665675,0.006385791,0.0001651759,0.0003367456,0.0004445851,0.0002330323,0.1446975,0.0140385,0.003662878,0.01471325,0.8142906],"study_design_scores_gemma":[0.00001318585,0.0000550611,0.0005676892,0.0000111227,0.00003181493,0.00008356074,0.00004176832,0.9908126,0.002640567,0.0039352,0.00179159,0.00001577742],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0513944,0.001637801,0.9296234,0.0006880137,0.0002636316,0.0002926265,0.0006627887,0.01192925,0.003508201],"genre_scores_gemma":[0.5719068,0.0005641466,0.4131032,0.0008923154,0.0002659438,0.0003772121,0.002668345,0.0005303142,0.009691721],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0129243,"threshold_uncertainty_score":0.02569818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03860166505143334,"score_gpt":0.278961099109769,"score_spread":0.2403594340583356,"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."}}