{"id":"W2247559579","doi":"10.4271/2010-01-0019","title":"Applying Virtual Statistical Modeling for Vehicle Dynamics","year":2010,"lang":"en","type":"article","venue":"SAE International Journal of Materials and Manufacturing","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Chrysler (Canada)","funders":"","keywords":"Vehicle dynamics; Dynamics (music); Computer science; Automotive engineering; Statistical model; Engineering; Simulation; Artificial intelligence; Physics; Acoustics","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":[0.0008093046,0.0005176261,0.0005553121,0.0008477442,0.0004349488,0.001031405,0.0009542629,0.0005782185,0.002899642],"category_scores_gemma":[0.00322835,0.0004015189,0.0009604371,0.000723184,0.0005677306,0.0008529579,0.0008343716,0.0006750507,0.0006648485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008450618,"about_ca_system_score_gemma":0.00125715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01206606,"about_ca_topic_score_gemma":0.006738492,"domain_scores_codex":[0.9994408,0.0002127247,0.00001959633,0.00007422044,0.0002043164,0.00004826448],"domain_scores_gemma":[0.9988617,0.0006864829,0.0001086304,0.0001339181,0.0001789152,0.000030431],"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":[0.00001011622,0.00001904592,0.0005452934,0.00001248681,0.0000175697,0.00002403509,0.00001784214,0.9524179,0.000525123,0.03206152,0.0003554307,0.01399368],"study_design_scores_gemma":[8.159191e-7,0.000003962165,0.00003612376,7.465975e-7,0.000001306334,0.000003991352,0.00000212945,0.9970868,0.0001013656,0.002400035,0.0003606812,0.000001994807],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006741432,0.00005132848,0.9902123,0.00007379883,0.00002794735,0.00002325563,0.00005681301,0.0002848295,0.002528352],"genre_scores_gemma":[0.7830361,0.0005607092,0.2030043,0.0001477203,0.0001252951,0.0003675699,0.0003116626,0.0002707379,0.01217606],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01206606,"threshold_uncertainty_score":0.02399164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05061769375328924,"score_gpt":0.3829470753249188,"score_spread":0.3323293815716296,"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."}}