{"id":"W4243621741","doi":"10.32920/ryerson.14644050.v1","title":"Enhancement of CN Tower lightning current derivative signals using a modified power spectral subtraction method","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Lightning and Electromagnetic Phenomena","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Lightning (connector); Tower; Waveform; Noise (video); SIGNAL (programming language); Acoustics; Current (fluid); Subtraction; Computer science; Power (physics); Meteorology; Electrical engineering; Mathematics; Engineering; Physics; Voltage; Artificial intelligence; Structural engineering","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":[0.0004684587,0.0006374883,0.0002777083,0.0006868528,0.000168578,0.0004288108,0.0006055745,0.0004788392,0.001260234],"category_scores_gemma":[0.001003011,0.0001508514,0.0004512793,0.0004472753,0.0002214772,0.0006369887,0.0003151279,0.000435605,0.000558325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003077836,"about_ca_system_score_gemma":0.0004111879,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001589096,"about_ca_topic_score_gemma":0.002086868,"domain_scores_codex":[0.9996044,0.00005713526,0.00001590869,0.00006457894,0.0002385588,0.00001939178],"domain_scores_gemma":[0.9996136,0.00009875625,0.00004573501,0.00006053129,0.0001638051,0.00001758161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004863289,0.0001720015,0.0018942,0.00027181,0.0000596992,0.0002811367,0.0002194321,0.05835192,0.367632,0.003330454,0.001413639,0.5658874],"study_design_scores_gemma":[0.00001924667,0.000296226,0.003691441,0.00001936524,0.00005092587,0.0004361618,0.00004752919,0.7804738,0.2084504,0.0006693451,0.005806136,0.00003943805],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08254673,0.0002335996,0.9118835,0.00006189023,0.00007951267,0.00005307319,0.0000528238,0.001289277,0.00379953],"genre_scores_gemma":[0.5787712,0.0004465637,0.4154846,0.00007340842,0.0000444925,0.00005534293,0.0002785994,0.0001658214,0.004679999],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9984109,"threshold_uncertainty_score":0.004215837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03548167794693572,"score_gpt":0.3265549095896271,"score_spread":0.2910732316426913,"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."}}