{"id":"W2186295185","doi":"","title":"PARAMETER ESTIMATION TECHNIQUES FOR NONLINEAR DYNAMIC MODELS WITH LIMITED DATA, PROCESS DISTURBANCES AND MODELING ERRORS","year":2013,"lang":"en","type":"article","venue":"QSpace (Queen's University Library)","topic":"Control Systems and Identification","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Queen's University","keywords":"Estimation theory; Computer science; Nonlinear system; Process (computing); Estimation; Control theory (sociology); Algorithm; Artificial intelligence; Engineering; Control (management)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.00002634763,0.0001382026,0.0001550339,0.0001225592,0.00009246349,0.0001233388,0.0002097767,0.0000715792,0.000005547695],"category_scores_gemma":[0.000006457434,0.000131783,0.00002073655,0.000151755,0.00002657968,0.00388746,0.00004398181,0.00007855733,0.000002157739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002758992,"about_ca_system_score_gemma":0.0000194672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007322162,"about_ca_topic_score_gemma":0.00004190834,"domain_scores_codex":[0.9993814,0.00001369631,0.0001034413,0.0002595578,0.0000886234,0.0001532593],"domain_scores_gemma":[0.9995186,0.00003465615,0.0000474195,0.0002895972,0.00004839657,0.00006131129],"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":[0.0002634973,0.0001330526,0.00189274,0.001771092,0.0003507519,0.00000846799,0.001734535,0.94665,0.0002186559,0.001412122,0.02604843,0.01951662],"study_design_scores_gemma":[0.0002077033,0.00002973773,0.0001439285,0.00007691503,0.00003405273,2.133502e-7,0.0003086296,0.9973702,0.0001680916,0.0006402597,0.000839011,0.0001812713],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2728904,0.00004648801,0.7215248,0.003689168,0.00003148908,0.0009254013,0.00008192266,0.0006469629,0.0001634369],"genre_scores_gemma":[0.9399076,0.0000618245,0.05835437,0.00001215988,0.00001670194,0.00001251656,0.0003233224,0.00002990703,0.001281585],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6670172,"threshold_uncertainty_score":0.5373957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01093173826838401,"score_gpt":0.1964065697303412,"score_spread":0.1854748314619572,"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."}}