{"id":"W1994594801","doi":"10.4271/2012-01-0900","title":"Mode Switching Control for Diesel Low Temperature Combustion with Fast Feedback Algorithms","year":2012,"lang":"en","type":"article","venue":"SAE International Journal of Engines","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ford Motor Company (Canada); University of Windsor","funders":"","keywords":"Mode (computer interface); Combustion; Diesel fuel; Automotive engineering; Control theory (sociology); Temperature control; Control (management); Feedback control; Computer science; Algorithm; Materials science; Environmental science; Engineering; Control engineering; Chemistry; 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":[0.0001570484,0.0002055742,0.0002652246,0.0002327805,0.00004148834,0.00003680728,0.0003990744,0.0001109333,0.00001485505],"category_scores_gemma":[0.0003721133,0.0001570813,0.0001236632,0.0001173341,0.00002835497,0.0006577408,0.00003185785,0.0004084358,0.000003732537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001456862,"about_ca_system_score_gemma":0.00002250169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001639335,"about_ca_topic_score_gemma":9.899348e-7,"domain_scores_codex":[0.9988436,0.000008944914,0.0003814982,0.0001090831,0.0003801285,0.0002768086],"domain_scores_gemma":[0.9986504,0.0002031362,0.0002457268,0.0001184101,0.0006910264,0.00009130849],"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":[0.0002772833,0.0001252691,0.0006947694,0.00003916329,0.0004132542,0.00001067866,0.0001863419,0.870196,0.1156703,0.003646847,0.0003624581,0.008377587],"study_design_scores_gemma":[0.02069216,0.000833414,0.008813106,0.00219523,0.0004497291,0.001871818,0.002354941,0.7178183,0.2279978,0.004677191,0.01032107,0.001975327],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.176875,0.0003946843,0.820257,0.0008876078,0.001217033,0.0001277609,0.00003784979,0.0001524893,0.00005063622],"genre_scores_gemma":[0.9631275,0.00003898298,0.035442,0.00006704176,0.001152134,0.00001604066,0.00001266597,0.00003922375,0.0001043994],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7862526,"threshold_uncertainty_score":0.640559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007763564246048097,"score_gpt":0.2578332452147119,"score_spread":0.2500696809686638,"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."}}