{"id":"W2095246268","doi":"10.1109/iclp.2012.6344391","title":"Calculation of tall-structure lightning current parameters using particle swarm optimization technique","year":2012,"lang":"en","type":"article","venue":"","topic":"Lightning and Electromagnetic Phenomena","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Particle swarm optimization; Classification of discontinuities; Lightning (connector); Tower; Current (fluid); Peak current; Reflection (computer programming); Computer science; Meteorology; Electrical engineering; Engineering; Physics; Structural engineering; Mathematics; Algorithm; Mathematical analysis","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":[0.0003499276,0.0005976244,0.0006088006,0.000585622,0.0002988569,0.0004778019,0.0004253034,0.0004593026,0.0007271199],"category_scores_gemma":[0.001126444,0.0003015642,0.0003483488,0.0003745018,0.0001936241,0.0005839944,0.0002299139,0.0003996342,0.0002357165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003235642,"about_ca_system_score_gemma":0.0007402213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005966646,"about_ca_topic_score_gemma":0.004595392,"domain_scores_codex":[0.999881,0.00002412937,0.000008165161,0.00002372354,0.00005223866,0.00001064407],"domain_scores_gemma":[0.9996885,0.0001314267,0.00004540046,0.00002275289,0.00009814264,0.00001372976],"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":[0.00003556078,0.00003167556,0.002061924,0.00004015578,0.00003753217,0.00004066777,0.00006554616,0.9171384,0.005167049,0.001921852,0.0006636897,0.07279595],"study_design_scores_gemma":[0.000003723621,0.000006598303,0.000365972,0.000001954367,0.000002937119,0.000004266332,0.000005466702,0.9983721,0.0007934311,0.000266262,0.0001741574,0.000003140829],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01950566,0.00004579288,0.9788903,0.00002825348,0.00001609419,0.00002875032,0.00002925693,0.0002193339,0.001236483],"genre_scores_gemma":[0.4792281,0.0001315877,0.5182016,0.00002759709,0.00002881598,0.0001431616,0.0002088858,0.00008900883,0.001941301],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005966646,"threshold_uncertainty_score":0.01186383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01562537486528011,"score_gpt":0.2597228555056678,"score_spread":0.2440974806403877,"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."}}