{"id":"W2755371172","doi":"10.1016/j.inffus.2017.09.010","title":"Dynamic classifier selection: Recent advances and perspectives","year":2017,"lang":"en","type":"article","venue":"Information Fusion","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":429,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Classifier (UML); Machine learning; Oracle; Artificial intelligence; Categorization; Data mining; Probabilistic logic","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008671128,0.00005514182,0.00004527794,0.00005244215,0.0009357556,0.0002978314,0.0002516889,0.00003075923,0.00002457313],"category_scores_gemma":[0.00003038638,0.00004920089,0.00001346979,0.00007410421,0.00004764969,0.004244224,0.0001396533,0.00006094628,0.00005829881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000394025,"about_ca_system_score_gemma":0.00002730823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005646915,"about_ca_topic_score_gemma":0.000006987775,"domain_scores_codex":[0.9995705,0.000007492292,0.0001187958,0.00009780263,0.0001226316,0.000082708],"domain_scores_gemma":[0.999428,0.00001125289,0.0001348112,0.0002494298,0.000137678,0.00003886749],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003601497,0.00002477817,0.0004295084,0.00001056264,0.000003493745,1.515043e-7,0.001584654,0.0001199662,0.0001015141,0.08709321,0.0008638903,0.9097646],"study_design_scores_gemma":[0.0002436151,0.00003702918,0.0892997,0.00001097059,0.000001914538,0.00002137317,0.000376503,0.3446274,0.00006076,0.005770853,0.5594286,0.0001212841],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01383871,0.001019546,0.9366876,0.01665417,0.000336694,0.0002604117,0.000005073325,0.0002012181,0.0309965],"genre_scores_gemma":[0.897762,0.008808926,0.09231437,0.000291035,0.00007061812,0.00006181765,0.00001619381,0.000004180192,0.0006708621],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9096434,"threshold_uncertainty_score":0.719717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01325651329638909,"score_gpt":0.2633503160558346,"score_spread":0.2500938027594455,"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."}}