{"id":"W2971502107","doi":"10.1049/iet-est.2018.5097","title":"ICE/HPM generator range extender for a series hybrid EV powertrain","year":2019,"lang":"en","type":"article","venue":"IET Electrical Systems in Transportation","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Magna International (Canada)","funders":"","keywords":"Prime mover; Automotive engineering; Generator (circuit theory); Range (aeronautics); Battery (electricity); Powertrain; Battery pack; Hybrid power; Auxiliary power unit; Electric generator; Engineering; Rectifier (neural networks); Permanent magnet synchronous generator; Power (physics); Electrical engineering; Mechanical engineering; Computer science; Torque; Magnet; Aerospace engineering; Voltage; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001099137,0.0002401242,0.0002656958,0.0001761257,0.0001448187,0.0002551489,0.0005574099,0.0001846475,0.003351584],"category_scores_gemma":[0.0001205109,0.00009971291,0.0002053082,0.0001251085,0.00009172427,0.000293958,0.0002765827,0.0003010331,0.0006684574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001398767,"about_ca_system_score_gemma":0.0001446535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005471829,"about_ca_topic_score_gemma":0.0008174758,"domain_scores_codex":[0.9999468,0.000007939791,0.000003021415,0.000008743237,0.00002781398,0.000005730489],"domain_scores_gemma":[0.9999671,0.000006750745,0.000004669883,0.000007694169,0.00001018128,0.000003661175],"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":[0.001075167,0.0004338647,0.007124381,0.0007656017,0.0001228402,0.001321299,0.0002060126,0.3286869,0.3597773,0.006381417,0.00684086,0.2872643],"study_design_scores_gemma":[0.000158436,0.001609916,0.007866095,0.00004503376,0.00008247812,0.001120892,0.00006875642,0.7853444,0.1557513,0.001777987,0.04612524,0.0000493901],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5922965,0.0006298522,0.3631375,0.0001877878,0.0001346574,0.0003473166,0.0005635252,0.00349766,0.03920515],"genre_scores_gemma":[0.9781687,0.00009354031,0.01430522,0.00001978305,0.000009566686,0.00007347519,0.0001950983,0.00005259791,0.007082097],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003351584,"threshold_uncertainty_score":0.01121223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0117870833080402,"score_gpt":0.2450738138874873,"score_spread":0.233286730579447,"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."}}