{"id":"W2493595568","doi":"","title":"Adaptive mutation for semi-separable problems","year":2001,"lang":"en","type":"article","venue":"Genetic and Evolutionary Computation Conference","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Mutation; Travelling salesman problem; Adaptive mutation; Heuristic; Operator (biology); Computer science; Fitness landscape; Mathematical optimization; Mutation rate; Separable space; Genetic algorithm; Mathematics; Artificial intelligence; Algorithm; Biology; Genetics; Population","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":[0.00128353,0.0006441001,0.0007821222,0.0006653059,0.0004852685,0.0007609537,0.0009678367,0.0008165897,0.002113493],"category_scores_gemma":[0.004423804,0.0002442691,0.0007016634,0.0005890808,0.001392965,0.001191844,0.001623455,0.001283141,0.000336907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006485225,"about_ca_system_score_gemma":0.0006274726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009689623,"about_ca_topic_score_gemma":0.0009044227,"domain_scores_codex":[0.9993085,0.0002325729,0.00003501017,0.000096248,0.0002678547,0.00005983132],"domain_scores_gemma":[0.9986387,0.0008870723,0.0001291922,0.0001145395,0.000151507,0.00007901552],"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":[0.0001409845,0.00008919601,0.0007349627,0.0002385871,0.00008854096,0.0004243715,0.0001915529,0.5069225,0.008508151,0.3846861,0.0024718,0.09550332],"study_design_scores_gemma":[0.00005072161,0.00006523799,0.0001220281,0.00001303277,0.00001138411,0.0001426888,0.00002377109,0.8911648,0.001107317,0.1045058,0.00278204,0.00001114416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03086978,0.0004835134,0.9634268,0.0003243188,0.00008774249,0.00006234466,0.0000238528,0.0001553886,0.004566188],"genre_scores_gemma":[0.5890303,0.0007047036,0.4004965,0.0002254005,0.0001360925,0.0002700691,0.0001118184,0.0001148968,0.008910323],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002113493,"threshold_uncertainty_score":0.007070303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03333412693013239,"score_gpt":0.2460461335273635,"score_spread":0.2127120065972311,"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."}}