{"id":"W2737244907","doi":"10.1049/iet-est.2017.0039","title":"Investigation and design of an axial flux permanent magnet machine for a commercial midsize aircraft electric taxiing system","year":2017,"lang":"en","type":"article","venue":"IET Electrical Systems in Transportation","topic":"Electric Motor Design and Analysis","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Canada Excellence Research Chairs, Government of Canada; Canada Research Chairs","keywords":"Automotive engineering; Engineering; Electric machine; Torque; Powertrain; Electric motor; Magnet; Finite element method; Range (aeronautics); Mechanical engineering; Aerospace engineering; Structural engineering; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002169377,0.0002240709,0.0002897188,0.0002242508,0.0002964208,0.0004103113,0.0003492091,0.000386859,0.001336295],"category_scores_gemma":[0.0003017391,0.0001369531,0.0002209693,0.00009700915,0.0002138425,0.0002473989,0.0001312485,0.00017501,0.0002495595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003069133,"about_ca_system_score_gemma":0.0005465356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001003556,"about_ca_topic_score_gemma":0.001113049,"domain_scores_codex":[0.9998618,0.00002535188,0.00000769575,0.00002590699,0.00006515109,0.00001395324],"domain_scores_gemma":[0.9998387,0.00003664594,0.00003196974,0.00001518416,0.00006444444,0.00001296884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005687681,0.0002424564,0.006192876,0.001622764,0.00009047771,0.001233065,0.000434496,0.2968124,0.48042,0.01086947,0.002775067,0.1987381],"study_design_scores_gemma":[0.00007459606,0.001616671,0.0056445,0.00004210993,0.0000626709,0.0006674308,0.0001809766,0.9255299,0.04602094,0.0009678531,0.01916715,0.00002516008],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4373178,0.00103533,0.5416192,0.0003444045,0.0001344561,0.0004639467,0.0001265868,0.0008264606,0.01813185],"genre_scores_gemma":[0.9383225,0.0001806829,0.0583156,0.00001824777,0.00001117399,0.00008588436,0.00005153079,0.0000155838,0.002998814],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001336295,"threshold_uncertainty_score":0.004470408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01825486590363787,"score_gpt":0.2261705014946226,"score_spread":0.2079156355909848,"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."}}