{"id":"W751528900","doi":"10.1016/j.tws.2015.06.011","title":"Numerical evaluation: AISI S400 steel-sheathed CFS framed shear wall seismic design method","year":2015,"lang":"en","type":"article","venue":"Thin-Walled Structures","topic":"Structural Load-Bearing Analysis","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Institute of Engineering Research, Seoul National University; Natural Sciences and Engineering Research Council of Canada; Federal Emergency Management Agency; Canada Foundation for Innovation; Compute Canada","keywords":"OpenSees; Shear wall; Incremental Dynamic Analysis; Seismic analysis; Structural engineering; Earthquake shaking table; Fragility; Seismic hazard; Earthquake simulation; Cold-formed steel; Engineering; Framing (construction); Seismic retrofit; Seismic loading; Geology; Reinforced concrete; Civil engineering; Finite element method","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001360288,0.0006059016,0.0008259313,0.0002930064,0.0001697606,0.0001886966,0.0006949331,0.0004049465,0.001170523],"category_scores_gemma":[0.0005827056,0.000520609,0.0002654989,0.0006443111,0.000074841,0.0002427797,0.00008501206,0.0008031237,0.000147065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004902554,"about_ca_system_score_gemma":0.0001695548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003912963,"about_ca_topic_score_gemma":0.000009023376,"domain_scores_codex":[0.9959401,0.000704386,0.0006514598,0.00064799,0.001342768,0.0007132397],"domain_scores_gemma":[0.9977499,0.0003989027,0.0001192665,0.0009483108,0.0003253733,0.0004581978],"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":[0.0000998728,0.000009256949,0.00007917197,0.00003543286,0.000514477,0.00001744265,0.003206388,0.97747,0.006522169,0.0003504569,0.005483471,0.006211894],"study_design_scores_gemma":[0.001558383,0.00009877632,0.003131945,0.00002421536,0.0004279928,0.00007787854,0.0002790484,0.9353933,0.02307217,0.03320093,0.001997769,0.0007375662],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6939893,0.004692497,0.2825024,0.001274377,0.003034855,0.002037514,0.0000346011,0.003364793,0.009069611],"genre_scores_gemma":[0.8866913,0.00001655953,0.1121953,0.0002738042,0.000359151,0.00005419763,0.00004711,0.0001181682,0.0002444601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.192702,"threshold_uncertainty_score":0.9997426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05190989967290321,"score_gpt":0.305653171091974,"score_spread":0.2537432714190708,"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."}}