{"id":"W4309761035","doi":"10.1109/ias54023.2022.9939715","title":"A Novel Regression Model-Based Toolbox for Induced Voltage Prediction on Rail Tracks Due to AC Electromagnetic Interference of Adjacent Power Lines","year":2022,"lang":"en","type":"article","venue":"2022 IEEE Industry Applications Society Annual Meeting (IAS)","topic":"Railway Engineering and Dynamics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Manitoba Hydro; University of Saskatchewan","funders":"","keywords":"Electric power transmission; Electromagnetic interference; Computer science; Interference (communication); Transmission line; Electronic engineering; Voltage; Line (geometry); Engineering; Electrical engineering; Telecommunications; Channel (broadcasting); Mathematics","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":[0.0008345291,0.001030505,0.000564215,0.0007534419,0.0002446623,0.0006631166,0.001153734,0.000832428,0.003176573],"category_scores_gemma":[0.003295236,0.0003580654,0.0008816624,0.0005942222,0.0001985193,0.0007188918,0.000670202,0.001154254,0.001723911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004486103,"about_ca_system_score_gemma":0.001012348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01056126,"about_ca_topic_score_gemma":0.009383854,"domain_scores_codex":[0.9996828,0.00007667187,0.00001934258,0.0001229592,0.00007145731,0.0000268326],"domain_scores_gemma":[0.9992331,0.0003333373,0.00008860297,0.00007052461,0.0002415688,0.0000328701],"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":[0.00009619483,0.0001066707,0.002298969,0.00009422025,0.00006864777,0.0001049224,0.00004550531,0.8681501,0.006151803,0.003049681,0.005085676,0.1147477],"study_design_scores_gemma":[0.000002360772,0.00000605683,0.000166489,0.000002185724,0.000002140254,0.000007180149,0.00000194365,0.9985878,0.000468843,0.0003400379,0.0004115972,0.00000332973],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008311176,0.00006858132,0.9852195,0.0000580428,0.00001846144,0.00003328401,0.0004752626,0.005038976,0.0007766096],"genre_scores_gemma":[0.3451102,0.0003282886,0.642676,0.0001592551,0.00005876281,0.0004894135,0.00447781,0.0008331077,0.005867218],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01056126,"threshold_uncertainty_score":0.02099955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01520000690139248,"score_gpt":0.243634277914233,"score_spread":0.2284342710128405,"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."}}