{"id":"W168149749","doi":"10.1007/978-0-387-71921-4_11","title":"Adaptive Control of Genetic Parameters for Dynamic Combinatorial Problems","year":2007,"lang":"en","type":"book-chapter","venue":"","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Travelling salesman problem; Mathematical optimization; Population; Scheme (mathematics); Selection (genetic algorithm); Genetic algorithm; Computer science; Diversity (politics); Quality control and genetic algorithms; Adaptive mutation; Evolutionary algorithm; Space (punctuation); Mathematics; Algorithm; Artificial intelligence; Meta-optimization","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000242527,0.0006541556,0.0005123334,0.0003452358,0.0001721991,0.0008008712,0.001208087,0.0006802291,0.00459932],"category_scores_gemma":[0.001019752,0.0002450763,0.0003317394,0.0007816982,0.0006378265,0.0006241014,0.0004324457,0.001237606,0.001040378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003523491,"about_ca_system_score_gemma":0.000262786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007568683,"about_ca_topic_score_gemma":0.001167914,"domain_scores_codex":[0.9998659,0.00002272233,0.000005111352,0.00002600546,0.00007047988,0.000009834751],"domain_scores_gemma":[0.9998201,0.0001063349,0.00001334529,0.00002482149,0.00002968829,0.000005840822],"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":[0.00003500018,0.00005329937,0.0001290088,0.0002029489,0.00003689578,0.00005916234,0.00008378669,0.3692663,0.01217165,0.1505823,0.01176787,0.4556117],"study_design_scores_gemma":[0.0000299284,0.00006499908,0.0002253579,0.00008342378,0.00002443987,0.0001189051,0.00002114792,0.8207742,0.003585765,0.1355295,0.03951599,0.00002638722],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006030966,0.007936297,0.9382917,0.0003536917,0.0003750273,0.00003406547,0.00004071512,0.0004379121,0.04649959],"genre_scores_gemma":[0.3781005,0.01512449,0.5189019,0.0004368656,0.0006393735,0.0003010517,0.000230165,0.0005197392,0.08574595],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00459932,"threshold_uncertainty_score":0.01538628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02221182163259981,"score_gpt":0.2421803554486267,"score_spread":0.2199685338160269,"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."}}