{"id":"W2129580388","doi":"10.1109/isic.1988.65498","title":"Genetic algorithms in system identification","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Identification (biology); Computer science; Genetic algorithm; Noise (video); Basis (linear algebra); Controller (irrigation); Algorithm; Colors of noise; Colored; System identification; Quality control and genetic algorithms; Artificial intelligence; Data mining; Machine learning; Mathematics; Meta-optimization; Noise reduction; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001648313,0.001070685,0.001204154,0.001109985,0.0004988199,0.001390505,0.0009810948,0.001781597,0.002527969],"category_scores_gemma":[0.00492494,0.0004024814,0.0005815745,0.001648448,0.001919125,0.001281407,0.0008807522,0.001742736,0.0007451071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001048412,"about_ca_system_score_gemma":0.001127198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005757598,"about_ca_topic_score_gemma":0.003070934,"domain_scores_codex":[0.9989849,0.0005206167,0.000042108,0.0001471776,0.0002585788,0.00004667443],"domain_scores_gemma":[0.9987908,0.0009469431,0.00006067326,0.00006932343,0.0001148805,0.0000173397],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003181342,0.00003901745,0.0006602178,0.0002573229,0.000123369,0.00009117919,0.0001357986,0.6303428,0.0006368021,0.2024503,0.004055825,0.1611755],"study_design_scores_gemma":[0.00003444562,0.00004950638,0.0002763979,0.0001086753,0.00002778391,0.00007408739,0.00004431329,0.6992141,0.0005870148,0.2834765,0.01608271,0.00002451576],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003003417,0.006545079,0.9798091,0.0007867196,0.0001509388,0.00004576943,0.00004736998,0.0003053987,0.009306272],"genre_scores_gemma":[0.2709546,0.0168854,0.6962209,0.0008215887,0.0006702591,0.000559733,0.0002893711,0.0002228979,0.01337525],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005757598,"threshold_uncertainty_score":0.01144814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01144242024072236,"score_gpt":0.2229709286101426,"score_spread":0.2115285083694202,"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."}}