{"id":"W4416649547","doi":"10.1109/tac.2025.3636986","title":"GREAT: Grassmannian Recursive Algorithm for Tracking and Online System Identification","year":2025,"lang":"","type":"article","venue":"IEEE Transactions on Automatic Control","topic":"Control Systems and Identification","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Grassmannian; Subspace topology; Linear subspace; Linear system; Online algorithm; Bounded function; Online model; Representation (politics); Gradient descent; System identification","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00075877,0.0005839295,0.0009675809,0.0008214806,0.0006974987,0.0006096996,0.0002767292,0.0003867788,0.00003055282],"category_scores_gemma":[0.00003442894,0.0006614032,0.0004206793,0.0005881675,0.00008261979,0.0004672404,0.000001257487,0.0003110918,0.00003930463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006963811,"about_ca_system_score_gemma":0.0001194522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001588325,"about_ca_topic_score_gemma":0.0002596556,"domain_scores_codex":[0.9964011,0.0002038593,0.001703919,0.0007813082,0.0003399946,0.0005698199],"domain_scores_gemma":[0.9975701,0.0006763242,0.000392383,0.0007588253,0.000423128,0.0001792476],"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":[0.00005374062,0.0002615377,0.000004452478,0.002189413,0.001160724,0.00000366923,0.0005643416,0.008289983,0.006746002,0.0005387924,0.0002595243,0.9799278],"study_design_scores_gemma":[0.005436248,0.0001291851,0.002101171,0.001931722,0.001786903,0.00002077438,0.001005442,0.9845684,0.001710336,0.0001433199,0.0006770909,0.0004894481],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008173116,0.00146283,0.9773622,0.0007885358,0.005760265,0.00446274,0.001231728,0.0006760405,0.00008256433],"genre_scores_gemma":[0.9946148,0.0001148381,0.001911709,0.00005642131,0.0001963506,0.001245836,0.00003159786,0.00008568914,0.001742714],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9864417,"threshold_uncertainty_score":0.9995837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01005054118442613,"score_gpt":0.242978804899694,"score_spread":0.2329282637152678,"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."}}