{"id":"W4404024354","doi":"10.3390/machines12110773","title":"Model Predictive Control Used in Passenger Vehicles: An Overview","year":2024,"lang":"en","type":"article","venue":"Machines","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Model predictive control; Control (management); Computer science; Transport engineering; Automotive engineering; Engineering; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.0001778455,0.0001543856,0.000221724,0.00009937606,0.00001969963,0.00009114132,0.0001165011,0.00007520796,0.000012847],"category_scores_gemma":[0.000005015984,0.0001337133,0.00006251317,0.0001452135,0.00001049974,0.0001908844,0.00001057831,0.0001765942,0.00002220829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000580243,"about_ca_system_score_gemma":0.000015175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009342614,"about_ca_topic_score_gemma":0.0003374367,"domain_scores_codex":[0.9992378,0.0000358096,0.000210146,0.0001867728,0.0001239313,0.0002055623],"domain_scores_gemma":[0.9996952,0.00004446219,0.000009207758,0.000177191,0.00001369358,0.00006025007],"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":[0.00001428068,0.00002823699,0.006223535,0.0002538323,0.00008340704,0.00003901107,0.0006467244,0.9680876,0.006886303,0.00525244,0.0001580883,0.01232658],"study_design_scores_gemma":[0.0004448961,0.00002235925,0.004429719,0.00009299516,0.00001625033,0.000003448009,0.00002236084,0.9932908,0.000005615765,0.001184985,0.0003389392,0.0001476005],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9553517,0.01390484,0.02627776,0.0002313734,0.0005956284,0.0004130448,0.0001639932,0.0009335058,0.002128207],"genre_scores_gemma":[0.9994189,0.0001038916,0.00003712859,0.0000513202,0.0001430682,0.00007750589,0.00001120728,0.00004836805,0.0001085942],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04406727,"threshold_uncertainty_score":0.545267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01635933366448521,"score_gpt":0.2488785145844609,"score_spread":0.2325191809199756,"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."}}