{"id":"W2085567163","doi":"10.1016/j.apenergy.2010.11.023","title":"Optimal location of Hybrid Flow Controller considering modified steady-state model","year":2010,"lang":"en","type":"article","venue":"Applied Energy","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"MATLAB; Control theory (sociology); Electric power system; Controller (irrigation); Mathematical optimization; Linear programming; Integer programming; Computer science; Power (physics); Control engineering; Hybrid power; Flow (mathematics); Engineering; Mathematics; Control (management)","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":[],"consensus_categories":[],"category_scores_codex":[0.0001236708,0.0001457229,0.0002464274,0.00006241011,0.0000408422,0.00002449552,0.000105559,0.00005189285,0.00002057361],"category_scores_gemma":[0.00001384265,0.0001514997,0.00003600182,0.0001137693,0.00005369672,0.00006249315,0.00002079933,0.0001078794,0.00000580916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002215094,"about_ca_system_score_gemma":0.0000386831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002152156,"about_ca_topic_score_gemma":0.00003724506,"domain_scores_codex":[0.9991665,0.000009171849,0.000333777,0.0001688884,0.0001315752,0.0001900533],"domain_scores_gemma":[0.9994768,0.00003714047,0.00004880458,0.0002657737,0.00009467317,0.00007682727],"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":[0.00001984074,0.00001776169,0.000002409746,0.00003460587,0.00002754596,4.221096e-7,0.0001457031,0.9648522,0.02080821,0.01318977,0.0001187938,0.0007827377],"study_design_scores_gemma":[0.0005919116,0.000004676064,0.000006437345,0.000004504515,0.000008014729,0.000002134883,0.00001806039,0.9652597,0.03285379,0.0006426165,0.000464242,0.0001439508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08906752,0.00003307519,0.8960562,0.000007962615,0.0001949478,0.00009927093,0.00001170212,0.0002019658,0.0143274],"genre_scores_gemma":[0.9868786,0.00000663501,0.0128606,0.00002788411,0.00001618499,0.00005431113,0.0000160468,0.0000308507,0.0001089095],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8978111,"threshold_uncertainty_score":0.6177977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008985020330488843,"score_gpt":0.1923494073171552,"score_spread":0.1833643869866664,"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."}}