{"id":"W2019632983","doi":"10.1007/s10596-014-9428-9","title":"Avalanche and landslide simulation using the material point method: flow dynamics and force interaction with structures","year":2014,"lang":"en","type":"article","venue":"Computational Geosciences","topic":"Fluid Dynamics Simulations and Interactions","field":"Engineering","cited_by":73,"is_retracted":false,"has_abstract":false,"ca_institutions":"dPoint Technologies (Canada)","funders":"Division of Civil, Mechanical and Manufacturing Innovation; National Science Foundation","keywords":"Material point method; Landslide; Hydrogeology; Displacement (psychology); Geology; Geotechnical engineering; Point (geometry); Deformation (meteorology); Flow (mathematics); Impact; Mechanics; Structural engineering; Engineering; Physics; Geometry; Mathematics; Finite element method","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":[0.0002753954,0.0004454228,0.0006707288,0.0004838772,0.0006070452,0.0007248803,0.001069248,0.00133726,0.003434751],"category_scores_gemma":[0.0009592551,0.0003747547,0.0004925561,0.0005940486,0.0005984101,0.0007802199,0.0007332954,0.0008163933,0.0002534341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003991663,"about_ca_system_score_gemma":0.0007540014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008693819,"about_ca_topic_score_gemma":0.005194065,"domain_scores_codex":[0.9998822,0.0000364088,0.000004584161,0.00001525236,0.00004334399,0.0000182086],"domain_scores_gemma":[0.9997177,0.0001427402,0.00002092592,0.00002019226,0.00005516033,0.00004329233],"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":[0.00004533056,0.00007426384,0.0009235673,0.00002511526,0.00001928551,0.0001111776,0.00004715395,0.9869356,0.001230286,0.00631432,0.0004345996,0.003839264],"study_design_scores_gemma":[0.0000111909,0.000008704602,0.0001449781,0.000001258133,0.000001640001,0.000007749265,0.000006611019,0.9988071,0.0001472105,0.0006913003,0.0001697776,0.000002537647],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7344439,0.000528231,0.2278825,0.000877345,0.000247072,0.0001627136,0.0006952138,0.0007240637,0.03443886],"genre_scores_gemma":[0.9547985,0.0002144313,0.03871978,0.00006734555,0.00005935606,0.0001156862,0.0002571576,0.000127363,0.005640549],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008693819,"threshold_uncertainty_score":0.01728642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01069686262610267,"score_gpt":0.2710310943781695,"score_spread":0.2603342317520668,"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."}}