{"id":"W2057936514","doi":"10.1007/s12239-015-0026-1","title":"Integrated ride and handling vehicle model using Lagrangian quasi-coordinates","year":2015,"lang":"en","type":"article","venue":"International Journal of Automotive Technology","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Department of Transportation","keywords":"Coupling (piping); Generalized coordinates; Euler angles; Motion (physics); Euler's formula; Lagrangian; Control theory (sociology); Engineering; Dynamic factor; Equations of motion; Vehicle dynamics; Simulation; Computer science; Automotive engineering; Applied mathematics; Mathematics; Mechanical engineering; Mathematical analysis; Classical mechanics; Physics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0002525979,0.000116032,0.000224686,0.0004821628,0.00002139715,0.00004704872,0.0002625637,0.0001248392,0.000002429859],"category_scores_gemma":[0.0001136619,0.000103785,0.00004978524,0.0001512233,0.00006556692,0.0001890731,0.00004705425,0.0002755923,0.00000228555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002094968,"about_ca_system_score_gemma":0.00005743416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004072368,"about_ca_topic_score_gemma":0.00002548194,"domain_scores_codex":[0.9992114,0.00001571512,0.0003394861,0.00008753934,0.0002001946,0.0001456105],"domain_scores_gemma":[0.9989252,0.00002429707,0.000135591,0.00006724765,0.000778228,0.00006945473],"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":[0.000155796,0.0001441098,0.02940548,0.00002314102,0.001301742,0.0004203211,0.00126049,0.7954342,0.0943573,0.00851711,0.0002893925,0.06869092],"study_design_scores_gemma":[0.000946039,0.00008546488,0.0003008974,0.00008359981,0.00002011542,0.0003782042,0.0005030541,0.9894413,0.001772216,0.006213639,0.0001520079,0.0001034605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9235423,0.0006565053,0.0743735,0.0005995607,0.0004947286,0.00004328701,0.00001062259,0.0001101183,0.0001693385],"genre_scores_gemma":[0.9967748,0.0000316882,0.003051514,0.0000253678,0.00007810927,0.000001251067,0.000001072335,0.0000190387,0.00001713926],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1940071,"threshold_uncertainty_score":0.4232228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01482734877856693,"score_gpt":0.2428351181574782,"score_spread":0.2280077693789113,"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."}}