{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009301977,0.0009849425,0.0008765912,0.0008760334,0.000683634,0.0008814423,0.001232462,0.001124492,0.001966653],"category_scores_gemma":[0.002295966,0.0005501387,0.0008869024,0.0004480541,0.0005465806,0.0006343412,0.000813767,0.0009922533,0.0005378213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007980813,"about_ca_system_score_gemma":0.001332699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007123721,"about_ca_topic_score_gemma":0.004882919,"domain_scores_codex":[0.9995291,0.0001049697,0.00002273577,0.0001152842,0.0001759719,0.00005194783],"domain_scores_gemma":[0.9993289,0.000295121,0.00007030759,0.0001248505,0.0001574643,0.0000233889],"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":[0.00003596692,0.00005111077,0.0007048647,0.0000351379,0.00003566474,0.00008032445,0.00007323684,0.9149578,0.01010038,0.003113781,0.0005306369,0.07028103],"study_design_scores_gemma":[0.000008431076,0.00001776285,0.0000989082,0.000004190097,0.000006191947,0.00001621508,0.000005934928,0.9967694,0.001676493,0.0006644792,0.0007262329,0.000005810376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01927405,0.00005850662,0.9750924,0.00005738507,0.00001942398,0.000107525,0.00003333301,0.002505514,0.002851819],"genre_scores_gemma":[0.4061475,0.0000819343,0.5909324,0.00007466395,0.00001357742,0.0002908697,0.0001379732,0.0003380662,0.001982997],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007123721,"threshold_uncertainty_score":0.01416451,"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."}}