{"id":"W1989271298","doi":"10.1177/1045389x14529032","title":"Feasibility study of utilizing superelastic shape memory alloy plates in steel beam–column connections for improved seismic performance","year":2014,"lang":"en","type":"article","venue":"Journal of Intelligent Material Systems and Structures","topic":"Seismic Performance and Analysis","field":"Engineering","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Shape-memory alloy; Structural engineering; Materials science; Flange; Ductility (Earth science); Beam (structure); Dissipation; Buckling; Hinge; Column (typography); Pseudoelasticity; Connection (principal bundle); Finite element method; Smart material; Composite material; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001326815,0.0003807905,0.0001087372,0.0002336766,0.0001236486,0.0001560798,0.0003743163,0.0002503447,0.0009195743],"category_scores_gemma":[0.0001728098,0.0001332794,0.0001393853,0.0001481171,0.0001373559,0.0002698198,0.0001185269,0.0001139932,0.0002056577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001189936,"about_ca_system_score_gemma":0.000162377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003461006,"about_ca_topic_score_gemma":0.001155376,"domain_scores_codex":[0.999933,0.000008257719,0.000002375895,0.000010033,0.00003681106,0.000009486084],"domain_scores_gemma":[0.9998959,0.00001464003,0.00002479004,0.00001451917,0.00003636985,0.0000138097],"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":[0.0001132658,0.00007397799,0.002424682,0.00007868896,0.00001274072,0.0001692831,0.00004750177,0.007909027,0.9751623,0.0003852011,0.0001221302,0.01350129],"study_design_scores_gemma":[0.00002761727,0.002263732,0.01461744,0.00001111774,0.00006575872,0.0002678843,0.0001311145,0.08571298,0.8938438,0.0001042306,0.00293411,0.00002013988],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941095,0.000111244,0.004879549,0.00001979349,0.00001146408,0.00001019879,0.00001699634,0.00004630954,0.0007947696],"genre_scores_gemma":[0.9948144,0.00006028239,0.004482598,0.000004350348,0.000002507198,0.000005021447,0.00002056984,0.000005114283,0.0006053083],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009195743,"threshold_uncertainty_score":0.003076315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01697898032889516,"score_gpt":0.2371689071253143,"score_spread":0.2201899267964191,"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."}}