{"id":"W2009999628","doi":"10.1109/acc.2010.5530656","title":"Incorporating term selection into nonlinear block structured system identification","year":2010,"lang":"en","type":"article","venue":"","topic":"Control Systems and Identification","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Lasso (programming language); Nonlinear system; Block (permutation group theory); Term (time); Selection (genetic algorithm); Algorithm; Laguerre polynomials; System identification; Polynomial; Computer science; Nonlinear system identification; Mathematical optimization; Linear model; Mathematics; Applied mathematics; Data modeling; Artificial intelligence; Machine learning","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":[0.001688103,0.0008488468,0.0008752,0.0005160452,0.0002742899,0.0005304562,0.0004643566,0.0006991129,0.001115821],"category_scores_gemma":[0.003628751,0.0003687438,0.0006277915,0.000569385,0.0004200163,0.0006974649,0.0007580616,0.0007015681,0.0005335761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002349787,"about_ca_system_score_gemma":0.0008298884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001468307,"about_ca_topic_score_gemma":0.002387347,"domain_scores_codex":[0.9992945,0.0003692412,0.00003252638,0.00007822717,0.0001917742,0.00003371957],"domain_scores_gemma":[0.9987366,0.0007964873,0.0001123135,0.0001079134,0.0002210884,0.00002564806],"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":[0.000118254,0.00007498246,0.0006251474,0.0001445293,0.0001319345,0.00009646954,0.0000966952,0.7630658,0.02292653,0.0150338,0.0009729118,0.196713],"study_design_scores_gemma":[0.000004918684,0.00004268656,0.00009155351,0.000004020931,0.00001053026,0.00001160934,0.000003045878,0.995241,0.001408212,0.002569409,0.0006070727,0.000005969947],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00381111,0.00007628612,0.9956727,0.00003568043,0.00001208267,0.00001532819,0.00001242961,0.0001196015,0.000244765],"genre_scores_gemma":[0.2523541,0.0005040203,0.7421691,0.0001108781,0.00009493663,0.00031855,0.0002737101,0.0001418043,0.00403286],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001688103,"threshold_uncertainty_score":0.008927703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003214986674580127,"score_gpt":0.1930359957946553,"score_spread":0.1898210091200752,"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."}}