{"id":"W3036447434","doi":"10.1142/s0218213020600040","title":"Selecting and Combining Classifiers Based on Centrality Measures","year":2020,"lang":"en","type":"article","venue":"International Journal of Artificial Intelligence Tools","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Centrality; Computer science; Classifier (UML); Artificial intelligence; Machine learning; Random subspace method; Cascading classifiers; Feature selection; Pattern recognition (psychology); Data mining; Mathematics; Statistics","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":[0.0005354939,0.00009517926,0.0001356903,0.0001114846,0.00007365394,0.0004141781,0.0005817706,0.00004424045,0.00004613857],"category_scores_gemma":[0.0009481948,0.00008298918,0.00007922594,0.0001550393,0.00004113406,0.0006240926,0.00005898322,0.0002621104,0.00003024594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003973135,"about_ca_system_score_gemma":0.00008653026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003760106,"about_ca_topic_score_gemma":0.000001139268,"domain_scores_codex":[0.9985204,0.000110272,0.0004612557,0.0001722321,0.0005968906,0.0001388984],"domain_scores_gemma":[0.9987081,0.0003516636,0.0002784957,0.00007225777,0.0004385717,0.0001509638],"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":[0.0003330728,0.000109392,0.0004977259,0.000005854357,0.00005658942,0.000080427,0.001394574,0.008737781,0.01428223,0.01703458,0.0005761221,0.9568917],"study_design_scores_gemma":[0.0002555645,0.0008156424,0.0008545942,0.0003356237,0.00002036192,0.00006260709,0.001134698,0.6436374,0.3211901,0.02823257,0.003102857,0.0003579978],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04443657,0.00002744213,0.9412481,0.01290989,0.000817382,0.00005671009,0.000004130392,0.00003049813,0.0004692578],"genre_scores_gemma":[0.9873937,0.00001777915,0.009806932,0.002545532,0.0002254481,9.626443e-7,0.000001344413,0.000004603694,0.000003711327],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9565337,"threshold_uncertainty_score":0.3993929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1424332155885543,"score_gpt":0.3272338505991412,"score_spread":0.1848006350105869,"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."}}