{"id":"W2144910496","doi":"10.1109/icpr.2014.225","title":"Generic Subclass Ensemble: A Novel Approach to Ensemble Classification","year":2014,"lang":"en","type":"article","venue":"","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Subclass; Classifier (UML); Computer science; Artificial intelligence; Ensemble learning; Perceptron; Machine learning; Pattern recognition (psychology); Benchmark (surveying); One-class classification; Statistical classification; Multiclass classification; Data mining; Support vector machine; Artificial neural network","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002604128,0.0001227466,0.0001229338,0.0001200683,0.0001105768,0.0001578363,0.0005191017,0.00007578439,0.00001100681],"category_scores_gemma":[0.00004436915,0.0001021563,0.00004365312,0.0004665744,0.00001175361,0.0003208751,0.0001398147,0.0000757423,0.0006478649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002610735,"about_ca_system_score_gemma":0.00002887894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002133358,"about_ca_topic_score_gemma":0.000004563133,"domain_scores_codex":[0.9987955,0.00004527781,0.0001828927,0.0004596431,0.0002557053,0.0002609867],"domain_scores_gemma":[0.9990904,0.00004947891,0.00005234596,0.0005518498,0.00009795288,0.0001579497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007948215,0.000286353,0.00007718654,0.00001812251,0.00000756117,3.022903e-7,0.0003963718,0.0003187362,0.6328434,0.1357997,0.04578643,0.1844578],"study_design_scores_gemma":[0.0005462663,0.0001145353,0.003087518,0.0000196581,0.000006355986,0.00002068883,0.00009861318,0.8406856,0.07668029,0.002311933,0.07599059,0.0004379798],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01267541,0.000005454636,0.8756201,0.001035521,0.0001962804,0.0001528607,5.506656e-7,0.0002150812,0.1100987],"genre_scores_gemma":[0.6915753,0.000002770038,0.3044417,0.001906678,0.00007235114,0.00005803334,0.00000840302,0.000008028166,0.001926756],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8403668,"threshold_uncertainty_score":0.8327209,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05217494820695119,"score_gpt":0.2483137750036264,"score_spread":0.1961388267966752,"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."}}