{"id":"W2144146926","doi":"10.1109/cdc.1989.70613","title":"Model reduction of linear discrete systems via weighted impulse response Grammians","year":2003,"lang":"en","type":"article","venue":"","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Eigenvalues and eigenvectors; Reduction (mathematics); Linear system; Impulse response; Realization (probability); Impulse (physics); Computer science; Mathematics; Applied mathematics; Algorithm; Control theory (sociology); Artificial intelligence; Statistics; 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":[0.0006156074,0.0008453208,0.0009134967,0.0004470407,0.0002855865,0.0008397179,0.0006864802,0.0006068699,0.002651208],"category_scores_gemma":[0.00130902,0.000406506,0.001293842,0.0004272847,0.0006638684,0.00105535,0.001026695,0.00141582,0.0008722541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004584636,"about_ca_system_score_gemma":0.000698052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00129335,"about_ca_topic_score_gemma":0.001309387,"domain_scores_codex":[0.9992798,0.0002872486,0.00004317394,0.0001272804,0.0002148377,0.00004776167],"domain_scores_gemma":[0.9996241,0.0001651952,0.00005104431,0.000080064,0.00006613162,0.00001344363],"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":[0.0001396372,0.00005988013,0.0002906785,0.0001890448,0.0001172123,0.0001412818,0.0001904516,0.704282,0.02319659,0.1273154,0.001452868,0.1426249],"study_design_scores_gemma":[0.00001175425,0.0000571594,0.00005602017,0.000008167121,0.00001269867,0.00002823288,0.00001283267,0.9644855,0.003828671,0.02866266,0.002824727,0.00001165333],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00234568,0.0000419328,0.9966819,0.00003114731,0.00001276797,0.00001395651,0.00001721639,0.0001659424,0.0006895236],"genre_scores_gemma":[0.3429046,0.000431265,0.6463245,0.0001216028,0.00005444507,0.0003837939,0.0003916066,0.0002860012,0.009102084],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002651208,"threshold_uncertainty_score":0.008869171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01655386266047291,"score_gpt":0.2560689584948668,"score_spread":0.2395150958343939,"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."}}