{"id":"W2165294756","doi":"10.1109/iecon.2006.348041","title":"A New High Frequency Modeling Technique of Travelling Waves in Long Cable PWM Drives","year":2006,"lang":"en","type":"article","venue":"Proceedings of the Annual Conference of the IEEE Industrial Electronics Society","topic":"Electromagnetic Compatibility and Noise Suppression","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"Canada Research Chairs","keywords":"Emtp; Waveform; MATLAB; Inverter; Electrical impedance; Voltage; Transient (computer programming); Electronic engineering; Frequency domain; Time domain; Pulse-width modulation; Modeling and simulation; Computer science; Lossless compression; Adjustable-speed drive; Engineering; Electrical engineering; Simulation; Electric power system; Physics; Power (physics)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004873677,0.0002273209,0.0004335849,0.00005098626,0.0000769195,0.00002486453,0.0008603891,0.0003256613,0.00001282474],"category_scores_gemma":[0.00007483152,0.0001683033,0.0002680501,0.0005694571,0.0001206943,0.000255916,0.00009152242,0.0008696905,9.887655e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001467446,"about_ca_system_score_gemma":0.0003948249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001933468,"about_ca_topic_score_gemma":0.0001336038,"domain_scores_codex":[0.9982873,0.00002044068,0.0006776208,0.0002219804,0.0003666669,0.0004260141],"domain_scores_gemma":[0.9990821,0.00006261357,0.0002758846,0.0002029794,0.0003407992,0.00003557381],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005261976,0.00008068793,0.00189383,0.0002226889,0.00005516305,5.441439e-8,0.00206504,0.05417835,0.9368348,0.003083786,0.0007026648,0.0008303948],"study_design_scores_gemma":[0.0005876271,0.0001410704,0.0002661366,0.0006177936,0.00005267455,0.000002282143,0.0004414024,0.04650805,0.9232087,0.02797149,0.000008456695,0.0001943602],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968414,0.0004162592,0.001339784,0.0001712846,0.0001320656,0.0005590757,0.00001443515,0.00003912686,0.0004866265],"genre_scores_gemma":[0.998019,0.0001298308,0.00159677,0.000003678619,0.0001039254,0.00001383827,0.000001238675,0.00002315562,0.0001085056],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0248877,"threshold_uncertainty_score":0.6863211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01613495219927435,"score_gpt":0.2077571964674594,"score_spread":0.1916222442681851,"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."}}