{"id":"W1966104103","doi":"10.1016/j.laa.2006.01.007","title":"Algorithms for model reduction of large dynamical systems","year":2006,"lang":"en","type":"article","venue":"Linear Algebra and its Applications","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":191,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Agence Nationale pour la Gestion des Déchets Radioactifs; Deutscher Akademischer Austauschdienst; University of Calgary","keywords":"Observability; Controllability; Mathematics; Reduction (mathematics); Model order reduction; Dynamical systems theory; Heuristic; Linear system; Algorithm; Matrix (chemical analysis); Gramian matrix; LTI system theory; Rank (graph theory); Low-rank approximation; Linear dynamical system; Mathematical optimization; Applied mathematics; Combinatorics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001490443,0.001363282,0.00182515,0.001325891,0.0008624208,0.001669442,0.001949577,0.001073483,0.006011163],"category_scores_gemma":[0.007363176,0.0007690331,0.001863905,0.00134179,0.001446126,0.00293456,0.002989953,0.003414805,0.001805398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001174841,"about_ca_system_score_gemma":0.001100454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002804687,"about_ca_topic_score_gemma":0.003830787,"domain_scores_codex":[0.9988778,0.0004904986,0.00006040729,0.0002120284,0.000284385,0.000074913],"domain_scores_gemma":[0.9966108,0.002433829,0.0001342445,0.0004737007,0.0002691357,0.000078233],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001156816,0.0001387713,0.0004551312,0.0003767306,0.0001554274,0.00007985444,0.0001783474,0.3810763,0.001388758,0.4243652,0.01074888,0.1809209],"study_design_scores_gemma":[0.00001777823,0.00001018266,0.00004729169,0.00001006964,0.00001240766,0.00001551976,0.0000124182,0.5737149,0.0003706322,0.4237022,0.002078051,0.000008505903],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002339592,0.0004235268,0.9942746,0.0002423768,0.00004673252,0.00003019985,0.00009733515,0.0005562768,0.001989448],"genre_scores_gemma":[0.2748525,0.001354476,0.7113601,0.0003505255,0.000371693,0.0005974374,0.001270012,0.0009156103,0.00892767],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006011163,"threshold_uncertainty_score":0.02010936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01533384924865086,"score_gpt":0.2759695880064222,"score_spread":0.2606357387577714,"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."}}