{"id":"W2509739029","doi":"10.1002/cjce.22639","title":"Iterative method for frequency domain identification of continuous processes with delay time","year":2016,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Control Systems and Identification","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Transfer function; Robustness (evolution); Frequency domain; Control theory (sociology); Nonlinear system; Time domain; Taylor series; Convergence (economics); Computer science; Identification (biology); Term (time); Iterative method; System identification; Least-squares function approximation; Algorithm; Mathematics; Mathematical optimization; Control (management); Engineering; Data modeling; Statistics","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":[0.0003610995,0.00008893183,0.0001878426,0.00009357466,0.00002426663,0.00003481999,0.0001638495,0.00004378721,0.000009119656],"category_scores_gemma":[0.0002416861,0.00005199281,0.00004725068,0.0001248812,0.00002382009,0.0001429853,0.00000179133,0.00006613481,0.000001714998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001239515,"about_ca_system_score_gemma":0.0001607484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009943306,"about_ca_topic_score_gemma":0.0001821155,"domain_scores_codex":[0.9993116,0.000009804582,0.0003760876,0.00005902556,0.00009539379,0.0001480785],"domain_scores_gemma":[0.9991308,0.000199991,0.0001339462,0.0001070703,0.0003141832,0.0001140301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000007877778,0.00000190408,0.00002142474,0.00009668138,0.00007504285,0.000001755031,0.0003348523,0.002164841,0.9958538,0.000537892,0.0001716483,0.0007323236],"study_design_scores_gemma":[0.001172925,0.00008118452,0.0001786218,0.0007442672,0.0001090321,0.0002052079,0.00003858683,0.01242578,0.9814317,0.001768256,0.001552885,0.0002915972],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4531542,0.0008148739,0.5450537,0.0004079303,0.000144579,0.0002773725,0.00004888618,0.00002372039,0.00007479236],"genre_scores_gemma":[0.9951876,0.000001818514,0.004605215,0.000003508588,0.0001195654,0.00001533539,0.000001534651,0.00002090557,0.00004456068],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5420334,"threshold_uncertainty_score":0.2120205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004040902746038559,"score_gpt":0.1870681401515118,"score_spread":0.1830272374054732,"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."}}