{"id":"W2028183259","doi":"10.4271/2013-01-2182","title":"Modelling Multi-Conductor Transmission Lines Using BLT Equation For Wire Diagnosis","year":2013,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Electrical Fault Detection and Protection","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Safran Electronics (Canada)","funders":"Safran","keywords":"Conductor; Electric power transmission; Electrical conductor; Transmission line; Materials science; Electronic engineering; Computer science; Electrical engineering; Engineering; Composite material","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":[0.0003605976,0.0006806778,0.0006763521,0.0002889254,0.0004926625,0.0001524458,0.0004254276,0.001002108,0.0004001562],"category_scores_gemma":[0.0003254264,0.0006080483,0.0004675631,0.000832476,0.00020204,0.0007895189,0.00005437041,0.001050128,0.00007874707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003801333,"about_ca_system_score_gemma":0.00004021683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001287949,"about_ca_topic_score_gemma":0.002598279,"domain_scores_codex":[0.9967355,0.00009564694,0.0009848515,0.0008311371,0.0005211532,0.0008317601],"domain_scores_gemma":[0.9982477,0.0004736647,0.0001255684,0.0006002282,0.0001883068,0.0003644965],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00009224104,0.0001642523,0.00001353785,0.0001221677,0.00003632877,0.000002059616,0.00002382745,0.02855365,0.9369075,0.0003430429,0.0004766224,0.03326481],"study_design_scores_gemma":[0.01308808,0.01045639,0.4353044,0.003485282,0.001260607,0.0003909498,0.0004597688,0.05973868,0.1094177,0.02624732,0.3285716,0.01157914],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9515423,0.001947294,0.02101901,0.003121985,0.001100754,0.006911685,0.0000777468,0.01152152,0.002757732],"genre_scores_gemma":[0.9583794,0.000671871,0.03821889,0.0003768437,0.0002589413,0.001702073,0.0000363557,0.0001831102,0.0001724947],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8274897,"threshold_uncertainty_score":0.9996371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04267187110257283,"score_gpt":0.2687002191865927,"score_spread":0.2260283480840199,"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."}}