{"id":"W2909422777","doi":"10.1109/epec.2018.8598302","title":"Routine for Simulating Transmission Lines with Symmetrical and Asymmetrical Configurations Using a Real and Constant Modal Transformation Matrix","year":2018,"lang":"en","type":"article","venue":"","topic":"Real-time simulation and control systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Renewable energy; Electric power transmission; Smart grid; Constant (computer programming); Power (physics); Photovoltaic system; Transformation (genetics); Computer science; Distributed generation; Electrical engineering; Power engineering; Power transmission; Electric power system; Transformation matrix; Electricity generation; Modal; Transmission (telecommunications); Topology (electrical circuits); Voltage; Engineering; Power factor; Physics; Materials science","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":[0.0008427833,0.00117324,0.0007030898,0.0007293775,0.0006385868,0.0007305528,0.001727086,0.00113166,0.04701369],"category_scores_gemma":[0.00230466,0.0005701344,0.0006012883,0.0006970709,0.0003335578,0.000736761,0.0005191685,0.001608659,0.00610715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004318091,"about_ca_system_score_gemma":0.0007688803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004565997,"about_ca_topic_score_gemma":0.005759665,"domain_scores_codex":[0.9998068,0.00005367967,0.00001782102,0.00003149627,0.000061827,0.00002831564],"domain_scores_gemma":[0.9987153,0.0008505451,0.00005518028,0.0001339813,0.0002055327,0.00003962852],"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":[0.0006804829,0.0004938726,0.004141019,0.001414967,0.0003710357,0.00062838,0.0009649258,0.5891216,0.03566197,0.04572996,0.0870372,0.2337545],"study_design_scores_gemma":[0.0002263157,0.00005832213,0.0004616686,0.00004870859,0.00003995658,0.0001285792,0.00006770269,0.9494547,0.01188818,0.007605762,0.02998194,0.00003813011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01298475,0.0000786735,0.9160217,0.0001377458,0.0001203353,0.0001838469,0.002897011,0.05567319,0.01190279],"genre_scores_gemma":[0.2039654,0.0001863016,0.765437,0.0001622779,0.00004923769,0.001387905,0.004633979,0.01050163,0.0136763],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04701369,"threshold_uncertainty_score":0.1572765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01650237032687462,"score_gpt":0.2735669168534976,"score_spread":0.257064546526623,"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."}}