{"id":"W4309145928","doi":"10.1016/j.compgeo.2022.105114","title":"A nonlocal Eulerian-based finite-element approach for strain-softening materials","year":2022,"lang":"en","type":"article","venue":"Computers and Geotechnics","topic":"Numerical methods in engineering","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland; Centre For Cold Ocean Resources Engineering","funders":"","keywords":"Finite element method; Eulerian path; Softening; Strain (injury); Structural engineering; Materials science; Mechanics; Classical mechanics; Mathematical analysis; Physics; Mathematics; Composite material; Engineering; Medicine; Lagrangian; Anatomy","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":[0.0003914937,0.0005387838,0.0008753585,0.0007696329,0.0005172108,0.0007435923,0.002264864,0.001356795,0.005137434],"category_scores_gemma":[0.0008413162,0.0005569707,0.0006171086,0.0006017766,0.0006806863,0.001159217,0.001405009,0.001029243,0.001316359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004198212,"about_ca_system_score_gemma":0.001104053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002086549,"about_ca_topic_score_gemma":0.005229866,"domain_scores_codex":[0.9998306,0.00003184484,0.000009447855,0.0000236561,0.00009121418,0.00001325004],"domain_scores_gemma":[0.9997484,0.00008380537,0.00001958748,0.00003670741,0.00009033127,0.00002121619],"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":[0.00005378443,0.0001908953,0.0004771073,0.0002710577,0.00004055822,0.0001460165,0.0001249951,0.8504876,0.02066631,0.05488474,0.001374599,0.07128232],"study_design_scores_gemma":[0.000004491446,0.00001080312,0.00004027759,0.000006205973,0.000003839379,0.00001465013,0.000006577031,0.9959776,0.0005701252,0.002105999,0.00125485,0.000004635364],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006082079,0.0001265344,0.9902005,0.0000782826,0.00005993829,0.00003833447,0.00003827674,0.0001416428,0.003234472],"genre_scores_gemma":[0.2091545,0.000632531,0.7714549,0.0002622445,0.0001012734,0.0003519317,0.0002266908,0.0005615459,0.01725441],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005137434,"threshold_uncertainty_score":0.01718646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01573373346215847,"score_gpt":0.2263231864874441,"score_spread":0.2105894530252856,"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."}}