{"id":"W1965748119","doi":"10.1109/tbme.2003.820384","title":"Identification of Hammerstein Models With Cubic Spline Nonlinearities","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Control Systems and Identification","field":"Engineering","cited_by":115,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Spline (mechanical); Nonlinear system; Algorithm; Control theory (sociology); Finite impulse response; Mathematics; Cubic function; Filter (signal processing); Non-linear least squares; Polynomial; Spline interpolation; System identification; Applied mathematics; Computer science; Estimation theory; Data modeling; Engineering; Mathematical analysis; Artificial intelligence","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":[0.0001174452,0.0001529611,0.0001998096,0.0002830502,0.00003907303,0.00002380079,0.00010657,0.0000965881,0.00001073642],"category_scores_gemma":[0.000002575631,0.0001440669,0.00006939731,0.0003639001,0.00004513544,0.0001915513,4.669694e-7,0.0001748549,0.00001442307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001010583,"about_ca_system_score_gemma":0.0000233447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005180963,"about_ca_topic_score_gemma":0.00001695525,"domain_scores_codex":[0.9989462,0.000004841815,0.0004193802,0.0001591612,0.0002848791,0.0001854774],"domain_scores_gemma":[0.9995634,0.00002479436,0.00003754061,0.0002271767,0.00005027442,0.00009683258],"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":[0.000009083459,0.00005898181,1.381354e-7,0.0001064474,0.0000533317,0.000001594434,0.000108949,0.8373901,0.1590862,0.0002326561,0.000005161647,0.002947261],"study_design_scores_gemma":[0.0008519963,0.00007468551,0.00002725546,0.0001658657,0.00004142641,0.00001270558,0.00005959081,0.8668,0.1314858,0.00005330266,0.0002353747,0.0001920416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07534015,0.0001031052,0.9234651,0.00008616853,0.0005100379,0.0001629653,0.0000403412,0.0002634857,0.00002859417],"genre_scores_gemma":[0.998305,0.00006645546,0.001398958,0.000004264334,0.00006523515,0.00005011747,0.000009690933,0.00003782107,0.00006243558],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9229649,"threshold_uncertainty_score":0.5874877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006625831009521541,"score_gpt":0.1834827169177502,"score_spread":0.1768568859082287,"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."}}