{"id":"W4407214852","doi":"10.23919/emc.2006.10852091","title":"CN Tower Lightning Current Derivative Heidler Model for the Validation of Wavelet De-Noising Algorithm","year":2006,"lang":"en","type":"article","venue":"","topic":"Earthquake Detection and Analysis","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Tower; Lightning (connector); Wavelet; Algorithm; Derivative (finance); Computer science; Current (fluid); Electrical engineering; Engineering; Artificial intelligence; Physics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002602559,0.00007245601,0.00009503505,0.00005292274,0.0001711152,0.00004164579,0.00007551322,0.00002725466,0.0005892797],"category_scores_gemma":[0.00002000173,0.00004519117,0.0000880018,0.000171806,0.00002998525,0.0001225639,0.00000377915,0.00005643565,0.000008606606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002984031,"about_ca_system_score_gemma":0.00002524937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007454386,"about_ca_topic_score_gemma":0.0005686802,"domain_scores_codex":[0.9993829,0.00002526705,0.0001781585,0.0001235252,0.0001408767,0.0001492506],"domain_scores_gemma":[0.999587,0.0001473888,0.00007726581,0.00008741831,0.00007390552,0.00002700447],"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":[0.00001415609,0.00002515875,0.01332812,0.00001013151,0.00003971766,2.563444e-7,0.0003810762,0.3057161,0.0002933052,0.0001656459,0.001109309,0.6789171],"study_design_scores_gemma":[0.0001138526,0.00001848469,0.01256006,0.000006376429,0.00002617148,9.332244e-7,0.0001140314,0.9779543,0.006572768,0.001117453,0.00144501,0.00007059749],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1245036,0.0002411831,0.8732937,0.0002217558,0.0000883805,0.0001091114,0.00003154868,0.00002184267,0.001488819],"genre_scores_gemma":[0.9815929,0.00002357362,0.01730009,0.00006974483,0.00009139714,0.000001618069,0.00005928026,0.000002049295,0.0008593854],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8570892,"threshold_uncertainty_score":0.64522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02128711035029097,"score_gpt":0.2393340123580542,"score_spread":0.2180469020077632,"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."}}