{"id":"W2885260234","doi":"10.1016/j.patcog.2018.08.004","title":"Online local pool generation for dynamic classifier selection","year":2018,"lang":"en","type":"article","venue":"Pattern Recognition","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"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":"Classifier (UML); Computer science; Artificial intelligence; Pattern recognition (psychology); Machine learning; Feature selection; Margin classifier; Data mining; Quadratic classifier","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":[0.001592621,0.001264711,0.002486189,0.001815175,0.001430206,0.001431065,0.00396596,0.001712607,0.02051483],"category_scores_gemma":[0.004228209,0.0006877263,0.001006834,0.001483809,0.0006665334,0.002224675,0.00294115,0.001434561,0.005919579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007508762,"about_ca_system_score_gemma":0.002258724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00295001,"about_ca_topic_score_gemma":0.005583938,"domain_scores_codex":[0.9988785,0.0002180915,0.00006525601,0.0003372916,0.0002744508,0.000226395],"domain_scores_gemma":[0.9980559,0.0007192625,0.00009078964,0.0005101122,0.0004579643,0.0001660222],"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":[0.00123017,0.0005135901,0.001994573,0.0001468237,0.0001163498,0.0004264352,0.0001777296,0.05466669,0.02251502,0.005568889,0.03831683,0.8743268],"study_design_scores_gemma":[0.0001540119,0.0002031827,0.0005911908,0.00001777618,0.00007570555,0.0001994574,0.00007163529,0.972609,0.01005972,0.01054651,0.005441536,0.00003020594],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04626938,0.0007381891,0.9378206,0.0003465202,0.0002392398,0.0003847978,0.0004750601,0.008963124,0.004763115],"genre_scores_gemma":[0.5781667,0.0002122016,0.4003839,0.000566943,0.0002823646,0.001124955,0.002897437,0.001190724,0.01517469],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02051483,"threshold_uncertainty_score":0.06862891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05118502926776238,"score_gpt":0.3059103123509797,"score_spread":0.2547252830832173,"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."}}