{"id":"W2093887230","doi":"10.1109/tpwrd.2012.2193672","title":"Fuzzy Dynamic Thermal Rating of Transmission Lines","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Power Delivery","topic":"Thermal Analysis in Power Transmission","field":"Engineering","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Electric power transmission; Transmission line; Fuzzy logic; Computation; Wind speed; Computer science; Line (geometry); Fuzzy set; Reliability engineering; Transmission (telecommunications); Engineering; Meteorology; Mathematics; Algorithm; Electrical engineering; Telecommunications","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":[0.0001744043,0.0002731669,0.000290067,0.0002397017,0.0001092793,0.00001262158,0.0001905924,0.000162783,0.0005775093],"category_scores_gemma":[0.000001127319,0.000245514,0.0002891413,0.0003152032,0.00005414452,0.0003793057,7.461746e-7,0.0003388432,0.00007812863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006276502,"about_ca_system_score_gemma":0.00001456247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001100982,"about_ca_topic_score_gemma":0.000003071026,"domain_scores_codex":[0.9986358,0.000056705,0.0004376709,0.0001776324,0.0002991619,0.0003930862],"domain_scores_gemma":[0.9993294,0.00009416555,0.00004642904,0.0003048973,0.00005287762,0.0001722196],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009046328,0.0003001245,0.00004313535,0.0001051084,0.0002239239,0.000003000426,0.001731693,0.2333831,0.6883761,0.00001153595,0.00006295805,0.07566893],"study_design_scores_gemma":[0.001105521,0.0001915388,0.001414528,0.0003728496,0.000383702,0.00002241413,0.0003692664,0.06213626,0.930362,0.0000422806,0.002725041,0.0008745758],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5356368,0.001011826,0.4596688,0.00002643409,0.0008087829,0.0001187203,0.00002471483,0.0002779599,0.002425962],"genre_scores_gemma":[0.9975328,0.0002459317,0.001880397,0.00003423071,0.00002778156,0.00001346721,0.000003678019,0.00006749183,0.0001942051],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.461896,"threshold_uncertainty_score":0.9999997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007801193453931051,"score_gpt":0.2164595033583764,"score_spread":0.2086583099044454,"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."}}