{"id":"W3038464966","doi":"10.1145/3377930.3389825","title":"Using implicit multi-objectives properties to mitigate against forgetfulness in coevolutionary algorithms","year":2020,"lang":"en","type":"article","venue":"","topic":"Cognitive Science and Mapping","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Elitism; Computer science; Coevolution; Function (biology); Algorithm; Artificial intelligence; Mathematical optimization; Mathematics; Biology","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":[0.0001718624,0.0001334506,0.0001535062,0.0001410893,0.0001553955,0.0001141292,0.0005503195,0.00003127327,0.000004053084],"category_scores_gemma":[0.0001130274,0.0001136073,0.0000443752,0.001053961,0.00005694837,0.0009016966,0.000531894,0.00009995927,0.00004403335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006541701,"about_ca_system_score_gemma":0.0001352935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001289174,"about_ca_topic_score_gemma":0.00004870392,"domain_scores_codex":[0.998651,0.00004815274,0.0001997916,0.0005172933,0.0002137179,0.0003699916],"domain_scores_gemma":[0.9994822,0.0000249376,0.00003293526,0.0001567235,0.0001234564,0.0001797146],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004265583,0.0003162377,0.009553375,0.0001072849,0.00003803029,0.0001480112,0.03675348,0.01385601,0.6458916,0.007952852,0.0004411143,0.2848993],"study_design_scores_gemma":[0.0003577359,0.00006181421,0.01138818,0.00009049186,0.000001344792,0.000006497929,0.001548682,0.9602612,0.02536015,0.0002809661,0.0003377914,0.0003051043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1859708,0.00005083576,0.8099458,0.002556657,0.00009835403,0.0003346855,0.000002194156,0.0001318077,0.0009089137],"genre_scores_gemma":[0.9241,0.000002008877,0.07193886,0.003808065,0.00004888414,0.00002883795,5.619907e-7,0.00000611863,0.00006660362],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9464052,"threshold_uncertainty_score":0.4632769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1172409756977934,"score_gpt":0.3009414176480281,"score_spread":0.1837004419502347,"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."}}