{"id":"W2391895653","doi":"10.1109/icvrv.2015.64","title":"Advances in Physically-Based Modeling of Deformable Soil for Real-Time Operator Training Simulators","year":2015,"lang":"en","type":"article","venue":"","topic":"Soil Mechanics and Vehicle Dynamics","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"CM Labs Simulations (Canada)","funders":"","keywords":"Terrain; Computer science; Simulation; Virtual reality; Real-time simulation; Unmanned ground vehicle; Operator (biology); Training (meteorology); Aerospace engineering; Range (aeronautics); Virtual machine; Work (physics); Human–computer interaction; Engineering; Artificial intelligence; Mechanical engineering; Physics","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":[0.0004210875,0.0008122664,0.00065857,0.0005042946,0.0003757725,0.001121014,0.001722181,0.001557024,0.00348452],"category_scores_gemma":[0.001445187,0.0007375358,0.00105047,0.000502279,0.000721809,0.001027153,0.001046059,0.00115258,0.0008991379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005789533,"about_ca_system_score_gemma":0.0009470278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0075208,"about_ca_topic_score_gemma":0.005910427,"domain_scores_codex":[0.9996597,0.00009554404,0.00002408409,0.00004119904,0.0001544296,0.00002506484],"domain_scores_gemma":[0.9994305,0.0002421993,0.00007271099,0.0001055218,0.00009341015,0.00005563521],"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":[0.00001150444,0.00003199376,0.0004777849,0.00005042025,0.00001794649,0.00007772982,0.0000619162,0.9774111,0.005281334,0.008212752,0.0002536246,0.008112006],"study_design_scores_gemma":[0.000004969707,0.000009415121,0.0000860471,0.00000694872,0.000003473089,0.00001957368,0.00001005167,0.9958231,0.0005875048,0.001189156,0.002251669,0.000008075783],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02219267,0.0003702238,0.9694301,0.0002111386,0.00009449884,0.00005946546,0.0001354672,0.0008383866,0.006668001],"genre_scores_gemma":[0.6784022,0.001590883,0.3115427,0.0001550687,0.0000882861,0.0002694014,0.0003931939,0.0005391225,0.007019115],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0075208,"threshold_uncertainty_score":0.01495403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02294999947210558,"score_gpt":0.245523014523981,"score_spread":0.2225730150518754,"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."}}