{"id":"W4381948107","doi":"10.4271/2023-01-1215","title":"Development of a Digital Twin to Support the Calibration of a Highly Efficient Spark Ignition Engine","year":2023,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Powertech Labs (Canada)","funders":"","keywords":"Turbocharger; Automotive engineering; Calibration; Powertrain; Homogeneous charge compression ignition; SPARK (programming language); Solver; Exhaust gas recirculation; Ignition system; Combustion; Spark-ignition engine; Computer science; Internal combustion engine; Engineering; Mechanical engineering; Gas compressor; Combustion chamber; Chemistry; Physics; Aerospace engineering","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":[0.0007604209,0.0006866787,0.0005727821,0.0005447722,0.0002580554,0.0007762993,0.001511535,0.0007337854,0.003658567],"category_scores_gemma":[0.0016068,0.0004159789,0.0005360822,0.0002985622,0.0002853108,0.0008311436,0.0008824861,0.0008131767,0.001073986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005247223,"about_ca_system_score_gemma":0.00114251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002027676,"about_ca_topic_score_gemma":0.001301148,"domain_scores_codex":[0.9996062,0.00004501342,0.00003001842,0.00006399358,0.0002234025,0.00003136808],"domain_scores_gemma":[0.9995839,0.00008401459,0.00002806308,0.0001063102,0.0001610262,0.00003667883],"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":[0.0004071177,0.0002242871,0.006786425,0.0003726357,0.0000817621,0.0003551513,0.0002941967,0.741894,0.1320469,0.006834419,0.003176921,0.1075262],"study_design_scores_gemma":[0.00004121038,0.0001438842,0.001078831,0.00002180974,0.00001611459,0.00009521517,0.00003146605,0.9292274,0.059813,0.0005375855,0.008955137,0.00003822177],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1720833,0.0001801572,0.8048935,0.0001720532,0.0002342146,0.0004309913,0.001106842,0.01104754,0.009851331],"genre_scores_gemma":[0.7019253,0.0002025329,0.2890676,0.00007983119,0.00001905729,0.0004267239,0.002307323,0.0007992728,0.005172314],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003658567,"threshold_uncertainty_score":0.0122391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01643137852302098,"score_gpt":0.2453461590681428,"score_spread":0.2289147805451218,"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."}}