{"id":"W591604045","doi":"","title":"GUIDE FOR THERMAL RATING CALCULATIONS OF OVERHEAD LINES","year":2014,"lang":"de","type":"article","venue":"Open Repository and Bibliography (University of Liège)","topic":"Engineering Applied Research","field":"Engineering","cited_by":112,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro One (Canada)","funders":"","keywords":"Overhead (engineering); Computer science; Reliability engineering; 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":[0.0005469564,0.0001748032,0.0003736765,0.003389266,0.0003287911,0.00008833549,0.0004815015,0.000168402,0.00001704504],"category_scores_gemma":[0.000001365587,0.00021091,0.0002095006,0.003849664,0.0001916352,0.0003176597,0.0002488189,0.000172452,0.000001507232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000878196,"about_ca_system_score_gemma":0.00002744152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001644487,"about_ca_topic_score_gemma":0.00001060403,"domain_scores_codex":[0.9989349,0.00006624233,0.0002637786,0.0002691119,0.0002143008,0.0002516179],"domain_scores_gemma":[0.998869,0.0003142012,0.0001451967,0.0003348679,0.0002082662,0.000128488],"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":[0.0004464372,0.0003838936,0.2144669,0.004261754,0.00239156,0.00002282814,0.002152216,0.0818724,0.6487574,0.00740209,0.03479952,0.003042956],"study_design_scores_gemma":[0.00769749,0.001504838,0.4446955,0.002222722,0.001582553,0.0000194869,0.003093661,0.4196994,0.0680221,0.000311845,0.04919075,0.001959659],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9036464,0.004219213,0.05911289,0.0003366651,0.0007268209,0.001431976,0.0001322418,0.0001122597,0.03028155],"genre_scores_gemma":[0.9759023,0.001089829,0.02222148,0.000003755938,0.0001454242,0.000001738606,0.00001376527,0.00002439111,0.0005973733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5807353,"threshold_uncertainty_score":0.8600661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01583373883868549,"score_gpt":0.2444674129202615,"score_spread":0.228633674081576,"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."}}