{"id":"W4313416446","doi":"10.20998/2079-0775.2022.2.01","title":"REVIEW OF MODERN USE OF GENETIC AND EVOLUTIONARY ALGORITHMS. STRATEGIES, POSSIBILITIES (REVIEW ARTICLE)","year":2022,"lang":"en","type":"article","venue":"Bulletin of the National Technical University «KhPI» Series Engineering and CAD","topic":"Engineering Technology and Methodologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hatch (Canada)","funders":"","keywords":"Computer science; Relevance (law); Randomness; Management science; Adaptation (eye); Artificial intelligence; Evolutionary algorithm; Data science; Machine learning; Mathematics; Engineering","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":[0.0006400693,0.001037683,0.001078798,0.003029842,0.0004219313,0.001747507,0.001299543,0.001563535,0.009640096],"category_scores_gemma":[0.002042328,0.0003818312,0.0007545147,0.004335607,0.0008095094,0.002520899,0.0006842662,0.001599613,0.003924108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009487732,"about_ca_system_score_gemma":0.001999951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00230789,"about_ca_topic_score_gemma":0.002238309,"domain_scores_codex":[0.9994389,0.0001189833,0.00007056935,0.0000985735,0.0002308447,0.00004207174],"domain_scores_gemma":[0.9990886,0.0004930557,0.00008951654,0.00003402195,0.0002547275,0.00003992226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005370259,0.00007356448,0.0002957496,0.01404936,0.0001046772,0.0003193977,0.000173643,0.001647869,0.0007624282,0.02315922,0.08888815,0.8704722],"study_design_scores_gemma":[0.000006181724,0.00004782402,0.0005478929,0.003230687,0.00005225123,0.0009857593,0.00009144961,0.0002914829,0.0002035567,0.008269227,0.9862522,0.00002143098],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002299234,0.9890807,0.001791792,0.0009831295,0.001324202,0.00001415557,0.00004702473,0.00002518243,0.006503865],"genre_scores_gemma":[0.003167049,0.9888498,0.002258343,0.0008709843,0.001521896,0.00002399472,0.00009459203,0.00001259142,0.003200605],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.009640096,"threshold_uncertainty_score":0.03224933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0233959527229744,"score_gpt":0.2192699176347676,"score_spread":0.1958739649117932,"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."}}