{"id":"W2018658285","doi":"10.1109/icpst.2006.321777","title":"Integrated Computer Approach to Analyze the Electromagnetic Impact of Transmission Lines","year":2006,"lang":"en","type":"article","venue":"","topic":"Aerosol Filtration and Electrostatic Precipitation","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Safe Engineering Services & Technologies (Canada)","funders":"","keywords":"Electromagnetic interference; Electromagnetic compatibility; Electric power transmission; Electromagnetic environment; Radiative transfer; Parametric statistics; Electromagnetic radiation; Electromagnetic field; Acoustics; Transmission (telecommunications); HVAC; Electronic engineering; Electromagnetic pulse; Electromagnetic noise; Computer science; Noise (video); Electrical engineering; Physics; Telecommunications; Engineering; Mechanical engineering; Optics; Mathematics","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":[0.00006290497,0.00009077259,0.00009956208,0.00005098573,0.00002424822,0.00002049403,0.00007710732,0.0000303374,0.00005529915],"category_scores_gemma":[0.000002601343,0.00005232332,0.00005941912,0.0003298037,0.00001091292,0.00004500598,0.000002435016,0.00006472239,0.000006759907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002907601,"about_ca_system_score_gemma":0.00001578695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001467883,"about_ca_topic_score_gemma":0.00001408399,"domain_scores_codex":[0.9995057,0.00002041633,0.0001811573,0.00007424059,0.00008457131,0.0001338946],"domain_scores_gemma":[0.9997908,0.00002809253,0.00001347422,0.0000928655,0.00004410517,0.0000305921],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002505327,0.00007459969,0.000198853,0.00002240917,0.00004260402,1.587365e-7,0.0005169618,0.4408422,0.5110509,0.001117553,0.02794121,0.01816747],"study_design_scores_gemma":[0.0001753918,0.0002224103,0.01864655,0.000006333571,0.00001277933,0.000003402982,0.00001727018,0.9593375,0.02100218,0.0002030478,0.000269396,0.0001036839],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.355823,0.00004026528,0.6382734,0.00005273037,0.00001661032,0.0001250012,0.000001751895,0.00009135289,0.00557589],"genre_scores_gemma":[0.972166,0.000005375802,0.02749423,0.00002836964,0.00003752347,0.000008204379,0.00004638697,0.00001084164,0.0002030549],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.616343,"threshold_uncertainty_score":0.2133683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006246896420644225,"score_gpt":0.2174619013810121,"score_spread":0.2112150049603679,"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."}}