{"id":"W2038409208","doi":"10.1049/ip-gtd:20045058","title":"Application of adverse and extreme adverse weather: modelling in transmission and distribution system reliability evaluation","year":2006,"lang":"en","type":"article","venue":"IEE Proceedings - Generation Transmission and Distribution","topic":"Power System Reliability and Maintenance","field":"Engineering","cited_by":142,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Adverse weather; Reliability (semiconductor); Reliability engineering; Extreme weather; Transmission (telecommunications); Computer science; Environmental science; Transmission system; Meteorology; Engineering; Telecommunications; Climate change; Geography; Ecology","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":[0.001108684,0.0002359811,0.0002800512,0.00007276669,0.0001506234,0.00002713568,0.0000534384,0.0002336613,0.000003670836],"category_scores_gemma":[0.000018876,0.0002250077,0.00004827507,0.0002581181,0.00007654208,0.0004669504,0.000009298394,0.0001388622,6.351414e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002558793,"about_ca_system_score_gemma":0.00002707842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001424704,"about_ca_topic_score_gemma":0.000008705127,"domain_scores_codex":[0.9982569,0.00004396228,0.0006880168,0.0004489647,0.0003406276,0.0002215331],"domain_scores_gemma":[0.9993708,0.00002232241,0.000126114,0.0001020466,0.0002618144,0.0001169279],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005879446,0.0004712349,0.01681969,0.007731353,0.00003815741,0.000001925571,0.002208952,0.2564847,0.5616428,0.02496557,0.0006361422,0.1284115],"study_design_scores_gemma":[0.001141777,0.00004403574,0.007430744,0.0002843644,0.00005813263,0.0000109173,0.0002378344,0.9702159,0.01756771,0.0004972405,0.002285423,0.0002259188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4956595,0.0009044148,0.5024742,0.00007092561,0.00004700893,0.0005980276,0.00006225215,0.00008845315,0.00009519132],"genre_scores_gemma":[0.9979553,0.0004264915,0.0007934967,0.000003166417,0.00005355187,0.0001144177,0.000628467,0.00001543727,0.000009644041],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7137312,"threshold_uncertainty_score":0.9175547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01289635902124462,"score_gpt":0.2059004522262654,"score_spread":0.1930040932050208,"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."}}