{"id":"W4321995222","doi":"10.5194/egusphere-egu23-9660","title":"Modeling the Impact of Geomagnetically Induced Currents on Electrified Railway Signalling Systems in the United Kingdom","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Railway Systems and Energy Efficiency","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"Natural Environment Research Council; Sight Research UK","keywords":"Geomagnetically induced current; Earth's magnetic field; Storm; Line (geometry); Ground; Space weather; Geomagnetic storm; Electric power system; Current (fluid); Interference (communication); Ionosphere; Meteorology; Power (physics); Electrical engineering; Physics; Engineering; Geophysics; Magnetic field; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001513684,0.0004884452,0.000589081,0.0005904778,0.00008339163,0.0001834842,0.001103504,0.0004082467,0.00001080291],"category_scores_gemma":[0.0001355223,0.0002612903,0.0003028551,0.0009907869,0.0000254842,0.00003423471,0.0001163273,0.001383839,0.00002035257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001763667,"about_ca_system_score_gemma":0.0001058207,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0245873,"about_ca_topic_score_gemma":0.0001121117,"domain_scores_codex":[0.9971543,0.0002788553,0.0009739338,0.0004029006,0.0006018829,0.0005881558],"domain_scores_gemma":[0.998374,0.0005117201,0.0001184799,0.0008114749,0.0001181159,0.00006616121],"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":[0.00001344595,0.00004222949,0.00004579194,0.0001735198,0.00009709052,0.00000522148,0.00053559,0.9948054,0.002423792,0.001582299,0.0001142555,0.0001613772],"study_design_scores_gemma":[0.0002485284,0.0001110829,0.0003189062,0.0006998506,0.0000225437,0.00000289958,0.0002241646,0.9978276,0.00009575849,0.0001335277,0.0000169529,0.000298152],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9842224,0.0002880321,0.01143147,0.00003442976,0.00122929,0.0007417285,0.00001367336,0.0002971543,0.001741777],"genre_scores_gemma":[0.9993631,0.00007011776,0.00001543473,0.000007392279,0.0002210606,0.0001487761,0.00004915535,0.0000897163,0.00003522998],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02447519,"threshold_uncertainty_score":0.9999839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08192640601600165,"score_gpt":0.2961528304321119,"score_spread":0.2142264244161102,"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."}}