{"id":"W1981414833","doi":"10.1109/tpwrd.2007.899535","title":"Selection of Line Insulators With Respect to Ice and Snow—Part I: Context and Stresses","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Power Delivery","topic":"High voltage insulation and dielectric phenomena","field":"Materials Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Arc flash; Electric power transmission; Selection (genetic algorithm); Snow; Line (geometry); Icing; Context (archaeology); Transmission line; Engineering; Computer science; Forensic engineering; Electrical engineering; Insulator (electricity); Meteorology; Artificial intelligence; Mathematics; Geology; Physics","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":[0.0002248094,0.0001297855,0.00016642,0.0002479039,0.000138641,0.00003272741,0.00005292222,0.00005599862,0.0002280361],"category_scores_gemma":[0.00001215648,0.0001124624,0.00001937074,0.0003838268,0.00007598181,0.0001866197,0.000001379739,0.00009517099,0.00001659123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003985644,"about_ca_system_score_gemma":0.00004091086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001281283,"about_ca_topic_score_gemma":0.0003338473,"domain_scores_codex":[0.99907,0.00003042981,0.0002424148,0.0002631621,0.0002028145,0.0001911296],"domain_scores_gemma":[0.9993486,0.0001856385,0.00006699798,0.000122722,0.0001382549,0.0001377764],"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":[0.003330239,0.0005841101,0.0009032457,0.00005525608,0.00008111731,0.00001987845,0.002911014,0.002677541,0.966336,0.0005180573,0.0002288929,0.0223547],"study_design_scores_gemma":[0.001007531,0.001361151,0.004246632,0.00008320121,0.00004270946,0.00003332725,0.0003692191,0.0002150889,0.9909891,0.00005023063,0.001342025,0.0002597643],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8825247,0.00006295722,0.116537,0.00005192082,0.0001667993,0.0001659919,0.00002726812,0.00005619701,0.0004071917],"genre_scores_gemma":[0.9989187,0.0000465208,0.0005687766,0.0002318238,0.0000184845,0.0000058555,6.490812e-7,0.00001318138,0.0001960736],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.116394,"threshold_uncertainty_score":0.4586085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01258299908996183,"score_gpt":0.2383537163289941,"score_spread":0.2257707172390323,"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."}}