{"id":"W3132391918","doi":"10.1109/tcns.2021.3124259","title":"Optimal Control of Network-Coupled Subsystems: Spectral Decomposition and Low-Dimensional Solutions","year":2021,"lang":"en","type":"preprint","venue":"IEEE Transactions on Control of Network Systems","topic":"Neural Networks Stability and Synchronization","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Adjacency matrix; Laplacian matrix; Eigenvalues and eigenvectors; Matrix (chemical analysis); Spectral graph theory; Matrix decomposition; Symmetric matrix; Mathematics; Coupling (piping); Degeneracy (biology); Eigendecomposition of a matrix; Graph theory; Topology (electrical circuits); Graph; Computer science; Applied mathematics; Discrete mathematics; Combinatorics; Physics; Voltage graph","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001380341,0.000625999,0.001756016,0.0002015387,0.0004543064,0.0002650689,0.0006873768,0.0006221678,0.00001985745],"category_scores_gemma":[0.00001035432,0.0006486335,0.0005850376,0.0006125814,0.0002289934,0.0004022376,0.00002884173,0.000918868,0.000002997822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002265444,"about_ca_system_score_gemma":0.0004313396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002748275,"about_ca_topic_score_gemma":0.0002459183,"domain_scores_codex":[0.9942157,0.001155908,0.001869437,0.001104473,0.0008117317,0.000842737],"domain_scores_gemma":[0.9955761,0.001120854,0.001153217,0.001171478,0.0007305379,0.0002478264],"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":[0.0002545375,0.0002896469,0.0001035276,0.0004880884,0.0005754021,0.00001715136,0.0001231876,0.9955239,0.0009583636,0.001101621,0.0001192603,0.0004452654],"study_design_scores_gemma":[0.002491501,0.0003423412,0.0003193879,0.001843919,0.000307643,0.00008243752,0.00002714925,0.9938345,0.0001287145,0.0001334517,0.00001420055,0.0004747439],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04376522,0.005676983,0.9417656,0.0002676382,0.006337212,0.001865459,0.0001307516,0.000164083,0.00002704339],"genre_scores_gemma":[0.9956042,0.0001733687,0.002923969,0.00007753826,0.0008955884,0.0002145753,0.00003920783,0.00004493637,0.00002665949],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.951839,"threshold_uncertainty_score":0.9995965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01240285406727708,"score_gpt":0.2254137171296498,"score_spread":0.2130108630623727,"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."}}