{"id":"W2613797664","doi":"10.1016/s1474-6670(17)31824-4","title":"Closed-Loop Subspace Identification: An Orthogonal Projection Approach","year":2004,"lang":"en","type":"article","venue":"IFAC Proceedings Volumes","topic":"Control Systems and Identification","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Alexander von Humboldt-Stiftung","keywords":"Singular value decomposition; Subspace topology; Mathematics; Projection (relational algebra); Kalman filter; Orthographic projection; Observability; Toeplitz matrix; Control theory (sociology); Orthogonal matrix; Matrix (chemical analysis); Algorithm; Computer science; Applied mathematics; Orthogonal basis; Artificial intelligence; Pure mathematics; Control (management); Mathematical analysis","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":[0.0006916546,0.001038136,0.001079092,0.0004769146,0.0005353232,0.0009546058,0.0007413614,0.0007197445,0.002545025],"category_scores_gemma":[0.00160391,0.000425538,0.000665272,0.0007464244,0.0006419919,0.001587911,0.00125071,0.00119612,0.0008420953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001712785,"about_ca_system_score_gemma":0.0008362823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001368923,"about_ca_topic_score_gemma":0.001266728,"domain_scores_codex":[0.9994394,0.0001962039,0.0000310973,0.0001083334,0.0001778252,0.00004708975],"domain_scores_gemma":[0.9995543,0.0001876194,0.0000353615,0.00006763077,0.0001376725,0.00001741755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003273872,0.0001915887,0.0004311196,0.0003784937,0.0001671961,0.0001717723,0.0002334185,0.3127425,0.02514034,0.0837428,0.002953958,0.5735195],"study_design_scores_gemma":[0.00001524739,0.00008077685,0.0001621907,0.00001389515,0.00002005779,0.00006428304,0.00002395203,0.9781648,0.003497581,0.01621936,0.001719488,0.00001845849],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001716055,0.0000956954,0.9970868,0.00002652367,0.00001803627,0.00001130643,0.00001196414,0.0001395655,0.0008939045],"genre_scores_gemma":[0.3204364,0.001182143,0.6709833,0.0001311597,0.000138641,0.0002316819,0.0002848929,0.0002273943,0.006384357],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002545025,"threshold_uncertainty_score":0.008513987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009987848689447461,"score_gpt":0.2099315086645817,"score_spread":0.1999436599751342,"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."}}