{"id":"W2530530944","doi":"10.11159/cdsr16.123","title":"Automated Model Tuning Using A Genetic Algorithm","year":2016,"lang":"en","type":"article","venue":"Proceedings of the International Conference of Control, Dynamic systems, and Robotics","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Ontario Centres of Excellence","keywords":"Computer science; Genetic algorithm; Algorithm; Machine learning","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":[0.0002129893,0.0001658556,0.0003009605,0.0001444493,0.00007834829,0.00009963651,0.0009502939,0.00007092418,0.000001331366],"category_scores_gemma":[0.0001661014,0.0001073371,0.00006104811,0.0001422222,0.0001556253,0.0005346517,0.0002629882,0.00007035118,4.959631e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001081912,"about_ca_system_score_gemma":0.0001282187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002101304,"about_ca_topic_score_gemma":8.150547e-7,"domain_scores_codex":[0.9985661,0.00001406785,0.0005035309,0.0002862306,0.0004517646,0.0001782875],"domain_scores_gemma":[0.997335,0.00008464255,0.0006761776,0.0001409137,0.001707533,0.00005569244],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002407884,0.00006918113,0.001283396,0.000090078,0.0002034342,0.00000104028,0.0003378745,0.8227298,0.06816994,0.0988737,0.00001510117,0.008202324],"study_design_scores_gemma":[0.0008998459,0.00002731973,0.0003763301,0.0003818976,0.00002339511,0.00004678079,0.00006736776,0.9955281,0.0002404166,0.002272437,0.00000320329,0.000132918],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004262118,0.00009637803,0.9940898,0.0004639242,0.0004437362,0.0002617561,0.00002747662,0.00009042172,0.0002643211],"genre_scores_gemma":[0.6588019,0.00004796911,0.3409063,0.00001794803,0.00001836153,0.000005793861,2.937671e-7,0.000009632055,0.0001918663],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6545398,"threshold_uncertainty_score":0.4377079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02311677357971546,"score_gpt":0.2637542770978292,"score_spread":0.2406375035181138,"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."}}