{"id":"W4223501105","doi":"10.3389/fbuil.2022.833167","title":"Probabilistic Fatigue Fragility Curves for Overhead Transmission Line Conductor-Clamp Assemblies","year":2022,"lang":"en","type":"article","venue":"Frontiers in Built Environment","topic":"Mechanical stress and fatigue analysis","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Fretting; Conductor; Probabilistic logic; Structural engineering; Electrical conductor; Engineering; Overhead (engineering); Residual; Transmission line; Electric power transmission; Dissipation; Catastrophic failure; Materials science; Computer science; Algorithm; Electrical engineering; Physics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000642612,0.0003485805,0.0002199238,0.001729624,0.0001797614,0.0003407714,0.0005440519,0.0007618633,0.001641702],"category_scores_gemma":[0.002049325,0.0001791191,0.0004803716,0.0005216328,0.0004339183,0.000485759,0.0003178386,0.0002619475,0.0002044252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005359547,"about_ca_system_score_gemma":0.0001736074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005106452,"about_ca_topic_score_gemma":0.00294219,"domain_scores_codex":[0.9998046,0.00004170675,0.00001190364,0.00003983286,0.0000751061,0.00002692544],"domain_scores_gemma":[0.9987397,0.0007624282,0.0002613217,0.00008136864,0.0001305699,0.00002467355],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002299692,0.000008877227,0.003132156,0.00001312381,0.00000457447,0.00007872385,0.00004774888,0.9903741,0.002140602,0.0007024712,0.00006561528,0.003409052],"study_design_scores_gemma":[9.290393e-7,0.00002315543,0.003225907,0.00000427156,0.000001938405,0.00003254124,0.00001311516,0.9957269,0.0005692802,0.0003165363,0.00007798008,0.000007313108],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8845456,0.0002225053,0.110492,0.00005830202,0.000003697953,0.0000250383,0.0003656068,0.0005119263,0.003775415],"genre_scores_gemma":[0.9973877,0.00004139021,0.002106985,0.000002208666,0.000001279028,0.00001057951,0.0001298252,0.00001119491,0.0003087537],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005106452,"threshold_uncertainty_score":0.01015347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03064867111787448,"score_gpt":0.2398492328241939,"score_spread":0.2092005617063194,"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."}}