{"id":"W1935137508","doi":"10.1109/ssap.1998.739357","title":"Adaptive system identification using interior point optimization","year":2002,"lang":"en","type":"article","venue":"","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Interior point method; Convergence (economics); Adaptive filter; Computer science; Point (geometry); Identification (biology); Filter (signal processing); Algorithm; Optimization problem; Mathematical optimization; Iterative method; System identification; Control theory (sociology); Mathematics; Artificial intelligence; Data modeling","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00003435315,0.00006241193,0.00006531236,0.00003080589,0.00007508829,0.00004367549,0.00004210081,0.00001600896,0.001950233],"category_scores_gemma":[4.321627e-7,0.00005606854,0.00004037486,0.00008192749,0.00001102861,0.0001635852,0.00001349269,0.00004473836,0.00006480898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002781122,"about_ca_system_score_gemma":0.000002332993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003574518,"about_ca_topic_score_gemma":1.690578e-7,"domain_scores_codex":[0.9995572,0.00002269467,0.0001508071,0.0001270545,0.00005834746,0.00008392605],"domain_scores_gemma":[0.9997532,0.000004766587,0.00006823764,0.0000992265,0.00004039394,0.00003419384],"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":[0.00001650459,0.00008343914,0.0002878699,0.00001350418,0.00006333036,7.687828e-7,0.0003963697,0.9033208,0.003435494,0.05718929,0.003134722,0.03205793],"study_design_scores_gemma":[0.00008887852,0.000006597755,0.000008187981,0.00001470057,0.000009077717,0.000001723344,0.0005749593,0.9977916,0.001353169,0.00003158395,0.00005606697,0.00006343727],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01940543,0.00001199933,0.9625763,0.00005594279,0.0002658608,0.0001105678,0.000002141414,0.00005373693,0.01751806],"genre_scores_gemma":[0.9941,9.441511e-7,0.003887345,0.00001389476,0.0002027163,0.000007137588,0.000006090964,0.000007931855,0.001773995],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9746945,"threshold_uncertainty_score":0.9989621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03821709954811816,"score_gpt":0.2393518126624207,"score_spread":0.2011347131143026,"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."}}