{"id":"W3122861757","doi":"10.4271/2021-01-0711","title":"A Methodology for Modelling of Driveline Dynamics in Electrified Vehicles","year":2021,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Electric and Hybrid Vehicle Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Powertrain; Vehicle dynamics; Computer science; Automotive engineering; Dynamics (music); Control engineering; Engineering; Torque; Physics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008359562,0.0006070996,0.001293015,0.0003951397,0.0001244896,0.00003378018,0.0008035225,0.001025744,0.00004382316],"category_scores_gemma":[0.001076635,0.0006011819,0.0004176507,0.001371959,0.0005057956,0.000215441,0.0001971605,0.001386334,0.000008087962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004957104,"about_ca_system_score_gemma":0.0001241799,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003294295,"about_ca_topic_score_gemma":0.04902912,"domain_scores_codex":[0.9962875,0.0001390703,0.001263958,0.0008633335,0.0004135023,0.001032687],"domain_scores_gemma":[0.997107,0.001429344,0.0001526548,0.0009879353,0.000180667,0.0001424538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002186251,0.0002029462,0.0001549121,0.0001476488,0.00006642238,0.00004596953,0.00001301352,0.004645688,0.9158601,0.06550463,0.0004377445,0.0127023],"study_design_scores_gemma":[0.005398281,0.004085606,0.7648848,0.0009332366,0.0004352284,0.0004626433,0.0007276823,0.00145882,0.06375389,0.1397342,0.01457102,0.003554568],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9759999,0.003595894,0.001482608,0.002954374,0.0002276366,0.001317362,0.0001254897,0.005120092,0.009176674],"genre_scores_gemma":[0.9364786,0.002125019,0.06041781,0.0002698738,0.00005898002,0.0003144638,0.00006833718,0.0001334684,0.0001335049],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8521062,"threshold_uncertainty_score":0.999644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03644170552892675,"score_gpt":0.2658713832462494,"score_spread":0.2294296777173227,"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."}}