{"id":"W2947132423","doi":"","title":"Neuro-governor: a neural adaptive controller for diesel engines","year":2003,"lang":"en","type":"article","venue":"Control and Intelligent Systems","topic":"Industrial Technology and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Governor; Diesel fuel; PID controller; Artificial neural network; Automotive engineering; Computer science; Control theory (sociology); Controller (irrigation); Control engineering; Engineering; Artificial intelligence; Biology; Control (management); Aerospace engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002233216,0.0002551159,0.0002857192,0.0001732063,0.0003251651,0.0003896902,0.0006396347,0.0005291057,0.001536862],"category_scores_gemma":[0.0004247388,0.000124394,0.0001417401,0.0001573591,0.0002093203,0.000329945,0.0003143196,0.0004549621,0.0003743346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002306518,"about_ca_system_score_gemma":0.0002506743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003703027,"about_ca_topic_score_gemma":0.007441625,"domain_scores_codex":[0.999943,0.000007764184,0.00000528137,0.00001488342,0.00002227203,0.000006833531],"domain_scores_gemma":[0.9999144,0.00002091051,0.00001041616,0.000008128504,0.00003977035,0.000006371313],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009483395,0.0002264549,0.003008277,0.0004612786,0.000177319,0.0003325242,0.0001921964,0.3222027,0.1033735,0.006305391,0.007859331,0.5549126],"study_design_scores_gemma":[0.0001153097,0.0003500839,0.001590412,0.00001713817,0.00007695326,0.0001050301,0.00001745209,0.9595182,0.02558132,0.0008474467,0.01175931,0.00002130383],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2234585,0.004370485,0.7493377,0.0006919306,0.0007880719,0.0001570434,0.0003211135,0.004853307,0.01602187],"genre_scores_gemma":[0.9674469,0.00048984,0.02184526,0.0001034943,0.00008804394,0.0000543144,0.0001154708,0.0000358572,0.009820864],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003703027,"threshold_uncertainty_score":0.007362962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01831673855131774,"score_gpt":0.2027167178221255,"score_spread":0.1843999792708077,"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."}}