{"id":"W2216656527","doi":"10.1504/ijpt.2015.073786","title":"Acausal powertrain modelling with cycle-by-cycle spark ignition engine model","year":2015,"lang":"en","type":"article","venue":"International Journal of Powertrains","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Powertrain; Automotive engineering; Driving cycle; Engineering; Torque converter; Internal combustion engine; Fuel efficiency; Torque; Power (physics); Electric vehicle; Physics; Clutch","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":[0.0002460462,0.0002373793,0.0002631421,0.0002971711,0.00002513467,0.00004183173,0.0006015564,0.000131071,0.00003453481],"category_scores_gemma":[0.0001825643,0.0002063308,0.0001053478,0.0001632649,0.00007133117,0.0006005861,0.00006147753,0.0005665814,0.00001352817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003236859,"about_ca_system_score_gemma":0.0001006685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007077231,"about_ca_topic_score_gemma":0.000001428941,"domain_scores_codex":[0.998161,0.00001410799,0.0005175305,0.0001886038,0.000834255,0.0002845295],"domain_scores_gemma":[0.9985615,0.00006714058,0.0002860504,0.0001670586,0.0007170407,0.0002011817],"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":[0.0001552031,0.0001069645,0.00001420342,0.00000372305,0.0001416334,0.00006524079,0.000274933,0.9820188,0.01035932,0.004548951,0.000941218,0.001369838],"study_design_scores_gemma":[0.00188128,0.0001723185,0.000004989353,0.0001173739,0.00002863397,0.0003394524,0.000331472,0.9715818,0.01212679,0.01159838,0.001533799,0.0002836917],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0799901,0.0001299327,0.9163197,0.001374579,0.0003597927,0.00006138916,0.00004217144,0.0001656809,0.001556614],"genre_scores_gemma":[0.9304461,0.00003717721,0.06895664,0.0001273174,0.000198176,0.000004371548,0.00002341729,0.00004911132,0.0001576467],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8504561,"threshold_uncertainty_score":0.8413926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02516938877364977,"score_gpt":0.2666342503534812,"score_spread":0.2414648615798314,"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."}}