{"id":"W1937580162","doi":"10.1002/nag.1089","title":"An efficient finite–discrete element method for quasi‐static nonlinear soil–structure interaction problems","year":2011,"lang":"en","type":"article","venue":"International Journal for Numerical and Analytical Methods in Geomechanics","topic":"Geotechnical Engineering and Underground Structures","field":"Engineering","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Finite element method; Nonlinear system; Computation; Benchmark (surveying); Stability (learning theory); Boundary (topology); Boundary value problem; Displacement (psychology); Soil structure interaction; Mixed finite element method; Extended finite element method; Domain (mathematical analysis); Discrete element method; Computer science; Applied mathematics; Mathematics; Mathematical optimization; Algorithm; Structural engineering; Mathematical analysis; Engineering; Mechanics; Physics; Geology","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":[0.0006801967,0.000432353,0.0006766307,0.000413439,0.0003524215,0.0004345808,0.001031272,0.0008572486,0.002856187],"category_scores_gemma":[0.0009500441,0.0003480937,0.0005907653,0.0003460902,0.0004958679,0.000487456,0.0007374286,0.0008278847,0.0009725578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003453424,"about_ca_system_score_gemma":0.0008066288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00211602,"about_ca_topic_score_gemma":0.002424517,"domain_scores_codex":[0.9997371,0.00007343699,0.00001463379,0.00002168112,0.0001341903,0.00001888799],"domain_scores_gemma":[0.9995982,0.0001812666,0.00002487999,0.00004389873,0.0001290957,0.00002263395],"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":[0.00007557971,0.000106702,0.0005549004,0.0002657183,0.0000400587,0.0001429281,0.0001377384,0.8498435,0.03065751,0.03072573,0.001895066,0.08555453],"study_design_scores_gemma":[0.000007768298,0.000009121199,0.00004259366,0.000005205624,0.000002149354,0.00001367434,0.00000378999,0.9960402,0.0008647625,0.001002612,0.002004501,0.0000036055],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004047198,0.00006660336,0.9939938,0.00004883431,0.00003245692,0.00004108906,0.00003076871,0.0001313199,0.001607893],"genre_scores_gemma":[0.1358029,0.0001745582,0.8587103,0.00005488286,0.00002940011,0.0003824173,0.0001443125,0.0001374192,0.004563777],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002856187,"threshold_uncertainty_score":0.009554923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0283870518619852,"score_gpt":0.3603036320720895,"score_spread":0.3319165802101043,"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."}}