{"id":"W2095665432","doi":"10.1109/59.852140","title":"State-space system identification-toward MIMO models for modal analysis and optimization of bulk power systems","year":2000,"lang":"en","type":"article","venue":"IEEE Transactions on Power Systems","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":101,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec","funders":"","keywords":"MIMO; Identification (biology); Realization (probability); Computer science; Control engineering; Computation; System identification; Time domain; State space; Modal; Transfer function; Electric power system; Control theory (sociology); State-space representation; Power (physics); Engineering; Data modeling; Control (management); Algorithm; Channel (broadcasting); Mathematics; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002300204,0.0006403261,0.000399468,0.0002044416,0.0002469989,0.0005594429,0.0003977169,0.0003253422,0.002707798],"category_scores_gemma":[0.0004301218,0.0002362878,0.0003816512,0.0001816729,0.0003607528,0.0004121495,0.0003599058,0.0008312237,0.0006190921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005291664,"about_ca_system_score_gemma":0.0005950839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009290005,"about_ca_topic_score_gemma":0.01116328,"domain_scores_codex":[0.9998778,0.00003871561,0.000004254132,0.00002045617,0.00004789291,0.00001080038],"domain_scores_gemma":[0.9998835,0.00005759242,0.00001514541,0.00001306311,0.00002621101,0.000004414575],"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":[0.00001997407,0.0000145332,0.0001509524,0.00004263834,0.000008815019,0.00002171403,0.00003941135,0.9572818,0.004175158,0.0202555,0.0004997331,0.01748977],"study_design_scores_gemma":[0.000002470116,0.000009455307,0.00006193173,0.000003635378,0.000001695984,0.000003592425,0.000005476712,0.9938536,0.000552549,0.004392686,0.001110266,0.000002683269],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004773658,0.00009617305,0.9909033,0.00008114061,0.00001225342,0.00002562535,0.00009480472,0.0002517355,0.003761297],"genre_scores_gemma":[0.7252632,0.0007250538,0.2565367,0.0001238507,0.00006055744,0.0003791628,0.0003675265,0.0001427236,0.01640132],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009290005,"threshold_uncertainty_score":0.0184719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0113325213268772,"score_gpt":0.2132103215093064,"score_spread":0.2018778001824292,"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."}}