{"id":"W4407873202","doi":"10.1016/j.ijrmms.2025.106062","title":"Simulation of time-dependent response of jointed rock masses using the 3D DEM-DFN modeling approach","year":2025,"lang":"en","type":"article","venue":"International Journal of Rock Mechanics and Mining Sciences","topic":"Rock Mechanics and Modeling","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University; Centre for Excellence in Mining Innovation","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Geology; Rock mass classification; Geotechnical engineering; Discrete element method; Mechanics; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.00128948,0.0001001634,0.0001975581,0.0003576892,0.0001054625,0.00005067865,0.0003821897,0.00005056597,0.000004152706],"category_scores_gemma":[0.0002671927,0.00007481695,0.00007043681,0.0001892454,0.0000054558,0.0001957607,0.0000980391,0.0001110982,1.095092e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004164901,"about_ca_system_score_gemma":0.0001173502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007184023,"about_ca_topic_score_gemma":0.000001042296,"domain_scores_codex":[0.9986917,0.00004642721,0.0005525657,0.0001103244,0.000483456,0.0001154989],"domain_scores_gemma":[0.9989194,0.0002505287,0.0002632899,0.00007147191,0.0004659503,0.00002937086],"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":[0.0000672377,0.0000152316,0.000009507487,0.00001392869,0.0000717767,9.194628e-7,0.0003571317,0.9605848,0.03784256,0.0006135153,0.000003052237,0.0004203032],"study_design_scores_gemma":[0.0002276428,0.00006274592,7.462402e-7,0.0002558569,0.0000363674,0.00002032997,0.001016683,0.9901458,0.00680115,0.001352427,0.00001505272,0.00006518757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.423937,0.0003028307,0.5753586,0.0000255673,0.0002929629,0.00003191319,0.000002243912,0.000004955832,0.00004388585],"genre_scores_gemma":[0.9891752,0.00009460252,0.01064438,0.00001723793,0.00003846384,6.221073e-7,4.178474e-7,0.000007495599,0.00002158634],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5652382,"threshold_uncertainty_score":0.3050947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03317438226506208,"score_gpt":0.2899917609030512,"score_spread":0.2568173786379891,"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."}}