{"id":"W4403930970","doi":"10.1016/j.finel.2024.104271","title":"3D analysis of reinforced concrete structural components using a multi-surface elasto-plastic-anisotropic-damage material model","year":2024,"lang":"en","type":"article","venue":"Finite Elements in Analysis and Design","topic":"Structural Behavior of Reinforced Concrete","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Structural engineering; Finite element method; Anisotropy; Materials science; Reinforced concrete; Composite material; Surface (topology); Engineering; Mathematics; Geometry; Physics","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":[0.0002222978,0.0003702657,0.0008726211,0.001285077,0.00006834369,0.0001596227,0.0002159745,0.0001370163,0.0003042368],"category_scores_gemma":[0.00003095653,0.0003520444,0.0002910352,0.002294829,0.00007411653,0.0002856835,0.00007845779,0.0001913238,0.000003111201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001334519,"about_ca_system_score_gemma":0.0000271582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002099956,"about_ca_topic_score_gemma":0.00001234451,"domain_scores_codex":[0.9978403,0.00007834212,0.0009048071,0.0003912224,0.0003683903,0.0004169134],"domain_scores_gemma":[0.9991805,0.0001957821,0.0001283266,0.0003224115,0.00005978327,0.0001132071],"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":[0.00004096336,1.766357e-7,0.004235358,0.00004609131,0.003255264,0.00001584304,0.0002354054,0.8510283,0.1409221,0.00004447767,0.000001736319,0.0001743286],"study_design_scores_gemma":[0.000509216,0.00003366258,0.005136668,0.00004073703,0.006123169,9.535153e-7,0.00004026512,0.9777047,0.01006079,0.000005717815,0.000005510902,0.0003386013],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6486479,0.00006097439,0.3507098,7.516434e-7,0.0001379139,0.0001427272,0.0002085802,0.00007590199,0.00001549661],"genre_scores_gemma":[0.9202126,0.00004058734,0.07939707,0.000007570024,0.00001601543,0.000005886051,0.0002213226,0.00003377712,0.00006523868],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2715646,"threshold_uncertainty_score":0.9998931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03533700179278364,"score_gpt":0.2738038350251675,"score_spread":0.2384668332323839,"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."}}