{"id":"W2796401905","doi":"10.4271/2018-01-1118","title":"Modeling of Tire-Wet Surface Interaction Using Finite Element Analysis and Smoothed-Particle Hydrodynamics Techniques","year":2018,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Fluid Dynamics Simulations and Interactions","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Smoothed-particle hydrodynamics; Finite element method; Mechanics; Particle (ecology); Materials science; Particle method; Surface (topology); Physics; Geology; Plasma; Mathematics; Thermodynamics; Geometry","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003685222,0.0004490213,0.0006443754,0.0003310879,0.0002628302,0.00008663922,0.0003236129,0.0003561804,0.0002154735],"category_scores_gemma":[0.0001711284,0.0004359993,0.0003040638,0.001149883,0.0004080301,0.000586117,0.000187432,0.0005691555,0.00001251102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003297866,"about_ca_system_score_gemma":0.00002665773,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001795154,"about_ca_topic_score_gemma":0.05054846,"domain_scores_codex":[0.9974622,0.0000658048,0.001007593,0.0005771414,0.0003942919,0.0004930153],"domain_scores_gemma":[0.9984717,0.0002387013,0.0001263548,0.0008146081,0.0001778281,0.0001708044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006744112,0.0001140524,0.0003104237,0.00002624771,0.0001647749,0.00000198951,0.00003634688,0.2299262,0.7666712,0.00155111,0.00002901327,0.001101256],"study_design_scores_gemma":[0.0006125045,0.001374216,0.282797,0.0003834518,0.001000843,0.00004123862,0.0002726773,0.7066174,0.002458192,0.001010485,0.002140912,0.001291172],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902311,0.00009057469,0.00126973,0.0002111803,0.0001487644,0.0004253178,0.00006821137,0.001360151,0.006194968],"genre_scores_gemma":[0.9849315,0.0002512849,0.01442103,0.0001086724,0.00006981337,0.0000367524,0.00003862006,0.00008708177,0.00005525571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.764213,"threshold_uncertainty_score":0.9998092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01407769938483464,"score_gpt":0.2687120782856416,"score_spread":0.2546343789008069,"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."}}