{"id":"W4394617173","doi":"10.4271/2024-01-2886","title":"Automotive Intermediate Shaft Design &amp; Bearing Selection for a Propulsion Switched Reluctance Motor in a Battery Electric Vehicle","year":2024,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Electric Motor Design and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Switched reluctance motor; Automotive industry; Automotive engineering; Bearing (navigation); Selection (genetic algorithm); Reluctance motor; Engineering; Mechanical engineering; Computer science; Control engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000415142,0.0004200606,0.0002726598,0.0004153874,0.0002110699,0.0006215906,0.0005802587,0.0003515088,0.004258187],"category_scores_gemma":[0.0005845699,0.0001535008,0.0002171109,0.0001894871,0.0001908101,0.0002734713,0.0002432716,0.0001822202,0.001461036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003713557,"about_ca_system_score_gemma":0.0004959733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008561082,"about_ca_topic_score_gemma":0.002485113,"domain_scores_codex":[0.9996905,0.00004089564,0.00002232717,0.00003557316,0.000175434,0.000035279],"domain_scores_gemma":[0.9996958,0.00003670715,0.00005177951,0.00002295726,0.0001734341,0.00001941394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009911447,0.0002455222,0.007634303,0.00125294,0.00003440505,0.0008411026,0.0004889998,0.0831405,0.6083116,0.01831575,0.009233768,0.26951],"study_design_scores_gemma":[0.0002729261,0.00795257,0.02744858,0.0002069279,0.0001852615,0.00232723,0.000743691,0.3026086,0.415919,0.00442764,0.2377552,0.0001522518],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5012066,0.001077183,0.4215873,0.0003273372,0.000287075,0.0007923285,0.0006139028,0.001984674,0.0721236],"genre_scores_gemma":[0.897992,0.0002794603,0.08919863,0.00003847949,0.00002109158,0.0001357714,0.0002787988,0.0001918786,0.01186396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004258187,"threshold_uncertainty_score":0.01424503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01338491949664773,"score_gpt":0.2406616026313092,"score_spread":0.2272766831346615,"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."}}