{"id":"W2041631839","doi":"10.4028/www.scientific.net/amm.44-47.2448","title":"Dynamic Model of the Road Feel Generation System in Advanced Driving Simulators","year":2010,"lang":"en","type":"article","venue":"Applied Mechanics and Materials","topic":"Real-time simulation and control systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Transportation of Ontario","funders":"","keywords":"Key (lock); Fidelity; High fidelity; Computer science; Simulation; System dynamics; Index (typography); Control engineering; Engineering; Artificial intelligence; Electrical engineering; Computer security; Telecommunications","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":[0.0002816933,0.0003588541,0.00037657,0.0002478316,0.0003171189,0.0005969321,0.0007477578,0.0006530567,0.003551604],"category_scores_gemma":[0.0003950617,0.0002899733,0.0003596075,0.0001722188,0.0003445921,0.0006809445,0.0005283479,0.000444823,0.0007548691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003794122,"about_ca_system_score_gemma":0.0006067658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006523645,"about_ca_topic_score_gemma":0.00244892,"domain_scores_codex":[0.9998019,0.00004279193,0.00001073491,0.00003999346,0.00008257553,0.00002199098],"domain_scores_gemma":[0.9999081,0.00002225613,0.00001320918,0.00001013672,0.00003956963,0.000006664422],"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":[0.00007159183,0.00002500177,0.0008069412,0.00006635954,0.00001623195,0.0001004244,0.0001303749,0.9596159,0.01202686,0.01324888,0.0006679864,0.01322345],"study_design_scores_gemma":[0.000008606777,0.0000255903,0.0001433841,0.000003923741,0.000004577595,0.00001192374,0.00001029861,0.9971445,0.0009102398,0.0004732785,0.001258357,0.00000539461],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04248125,0.0001380189,0.9398159,0.0001857125,0.00005552507,0.00009226512,0.0001581186,0.0007211975,0.01635212],"genre_scores_gemma":[0.9523507,0.0002595733,0.03229816,0.00007057022,0.00001921913,0.0003071342,0.0002118453,0.00006944844,0.01441348],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006523645,"threshold_uncertainty_score":0.01297134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004753441139201775,"score_gpt":0.1885316886239851,"score_spread":0.1837782474847833,"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."}}