{"id":"W2198379938","doi":"10.1016/j.engstruct.2015.10.048","title":"Earthquake-resistant design of buckling-restrained braced RC moment frames using performance-based plastic design method","year":2015,"lang":"en","type":"article","venue":"Engineering Structures","topic":"Seismic Performance and Analysis","field":"Engineering","cited_by":81,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"University of British Columbia; National Natural Science Foundation of China; Ministère de l’Éducation, Gouvernement de l’Ontario; University of Michigan","keywords":"Structural engineering; Moment (physics); Dissipation; Bilinear interpolation; Braced frame; Ductility (Earth science); Shear wall; Seismic analysis; OpenSees; Nonlinear system; Engineering; Buckling; Frame (networking); Computer science; Finite element method; Materials science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003957261,0.0003716651,0.0004674795,0.000401491,0.00005523828,0.0000451091,0.0002467906,0.0001446554,0.00002948475],"category_scores_gemma":[0.0001194122,0.0003483463,0.000110775,0.0004623897,0.00003219928,0.000167148,0.00002162642,0.0002599966,0.000003620491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001318066,"about_ca_system_score_gemma":0.0001060432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000223083,"about_ca_topic_score_gemma":2.436287e-7,"domain_scores_codex":[0.998399,0.00004471981,0.000455769,0.0002404596,0.0003989237,0.000461168],"domain_scores_gemma":[0.9990928,0.0002520915,0.00008009633,0.0003215966,0.00007863786,0.0001748138],"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":[0.00005732996,0.000007443162,0.00005182813,0.0001326843,0.0001505675,0.0000062276,0.0002494607,0.9601858,0.03790164,0.00003205417,0.00008569971,0.001139297],"study_design_scores_gemma":[0.0005839686,0.0001124143,0.001237665,0.0001043295,0.0001033508,0.000006350028,0.0000551754,0.9219483,0.07528163,0.00005228689,0.0001610039,0.0003535371],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3496867,0.0002692594,0.6494151,0.000005264318,0.000274337,0.000120859,0.000007081481,0.0002128356,0.000008492306],"genre_scores_gemma":[0.7361472,0.00001177791,0.2636374,0.00001369958,0.000107917,0.00001182643,0.000007306723,0.00005570861,0.00000723415],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3864604,"threshold_uncertainty_score":0.9998968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03044240629101876,"score_gpt":0.2420116299162135,"score_spread":0.2115692236251948,"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."}}