{"id":"W1976538031","doi":"10.1002/cjce.5450800115","title":"Perturbation signal design for neural network based identification of multivariable nonlinear systems","year":2002,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Control Systems and Identification","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Multivariable calculus; Control theory (sociology); Nonlinear system; Perturbation (astronomy); Artificial neural network; Computer science; SIGNAL (programming language); Control engineering; System identification; Identification (biology); Engineering; Control (management); Artificial intelligence; Physics; Data modeling","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005147399,0.00009787983,0.0001873852,0.00009346395,0.00004665436,0.00006918367,0.0001805755,0.0000712011,0.00001476991],"category_scores_gemma":[0.0001368537,0.00008327283,0.00008528129,0.0001527551,0.00001540092,0.000111573,0.000001794806,0.0001369441,0.000001628165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001520563,"about_ca_system_score_gemma":0.00004172613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001445569,"about_ca_topic_score_gemma":0.0000110184,"domain_scores_codex":[0.9990572,0.0000184337,0.0005362793,0.00006050281,0.0001268237,0.0002007501],"domain_scores_gemma":[0.9992099,0.0001912955,0.0001508506,0.0001238492,0.0001884005,0.0001357279],"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":[0.000004043073,0.00000250869,0.000006903056,0.00006317308,0.0000261616,5.552723e-7,0.0000616642,0.8607861,0.1379054,0.0001021912,0.0007960002,0.0002452676],"study_design_scores_gemma":[0.000273272,0.00001400139,0.0000237499,0.00007418085,0.00003332674,0.00001170649,0.000004914127,0.9725971,0.02620343,0.00001786091,0.0006669135,0.0000795255],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1929751,0.004792353,0.7985431,0.0003278833,0.002324185,0.0008800765,0.00003963771,0.00006608196,0.00005156103],"genre_scores_gemma":[0.9981861,0.000001401419,0.001215793,0.000005238935,0.0005119733,0.00001521994,0.000004316084,0.00002469812,0.0000353364],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8052109,"threshold_uncertainty_score":0.3395767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0160309155460586,"score_gpt":0.1755442302647111,"score_spread":0.1595133147186525,"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."}}