{"id":"W4383901038","doi":"10.1016/j.compgeo.2023.105617","title":"Comparison of local and nonlocal regularization approaches in Eulerian-based finite element analyses","year":2023,"lang":"en","type":"article","venue":"Computers and Geotechnics","topic":"Geotechnical Engineering and Underground Structures","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Shear band; Shearing (physics); Finite element method; Shear (geology); Scaling; Materials science; Mechanics; Eulerian path; Regularization (linguistics); Softening; Viscoplasticity; Geotechnical engineering; Geology; Structural engineering; Geometry; Mathematics; Physics; Mathematical analysis; Computer science; Composite material; Engineering; Constitutive equation; Lagrangian","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":[0.001872287,0.0005280768,0.0007090961,0.0009258673,0.0003685712,0.0009721418,0.001051017,0.0009784003,0.001764897],"category_scores_gemma":[0.003952263,0.0002716276,0.0005812155,0.0006254629,0.0006843311,0.001321898,0.001033845,0.0007043926,0.0004026028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003911501,"about_ca_system_score_gemma":0.0008722994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001874243,"about_ca_topic_score_gemma":0.00504893,"domain_scores_codex":[0.9993588,0.0002806103,0.00003363137,0.0000596437,0.000230649,0.00003667967],"domain_scores_gemma":[0.9971675,0.001635406,0.0001572451,0.0002891953,0.0006639916,0.00008654274],"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":[0.0008297079,0.0005872842,0.004437428,0.0007201587,0.0002222889,0.00009599604,0.0004227243,0.5418808,0.04867234,0.030572,0.001324737,0.3702344],"study_design_scores_gemma":[0.00001955863,0.0000795913,0.0009835293,0.00002990817,0.00003677284,0.00004373668,0.00004918676,0.9896952,0.005690329,0.002432544,0.0009182502,0.00002142079],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07034244,0.0008946586,0.92497,0.0001626348,0.00003946,0.00003406709,0.00003887973,0.0004425105,0.003075212],"genre_scores_gemma":[0.5877695,0.001156886,0.4044116,0.0001149878,0.00006165424,0.0001021366,0.0001729238,0.0006630504,0.005547247],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001874243,"threshold_uncertainty_score":0.009901702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04675878944626431,"score_gpt":0.2749169713283679,"score_spread":0.2281581818821036,"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."}}