{"id":"W3214132239","doi":"10.14288/1.0401124","title":"Improved regenerative braking in electric vehicles through switch selection optimization","year":2021,"lang":"en","type":"article","venue":"Open Collections","topic":"Electric and Hybrid Vehicle Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Regenerative brake; Engine braking; Selection (genetic algorithm); Automotive engineering; Computer science; Engineering; Brake; 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":[0.0003871706,0.0006459139,0.000497405,0.0003441897,0.0002558825,0.0007939254,0.0005071058,0.000383277,0.002470646],"category_scores_gemma":[0.00056727,0.000377877,0.0006643644,0.0003199854,0.0003348441,0.000405197,0.0004600732,0.0005128232,0.0002630115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004673642,"about_ca_system_score_gemma":0.0006625673,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002922278,"about_ca_topic_score_gemma":0.002822867,"domain_scores_codex":[0.9998817,0.00003839664,0.00000481008,0.00001962075,0.00003284289,0.00002256529],"domain_scores_gemma":[0.9998795,0.00007076573,0.00001846341,0.000007546315,0.00001822714,0.000005484519],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001507358,0.00001326295,0.0001523035,0.00002556852,0.000007006116,0.00001151666,0.00001181268,0.9892622,0.001144088,0.002769607,0.000142748,0.006444825],"study_design_scores_gemma":[0.00000434527,0.00002134984,0.00006130424,0.00000485499,0.000004718303,0.000003634843,0.000006332347,0.9978333,0.0004520817,0.001076794,0.0005294363,0.000001924117],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07691576,0.0005790958,0.8959352,0.0001790042,0.00004394335,0.0000904114,0.00009845571,0.000391726,0.02576644],"genre_scores_gemma":[0.9085801,0.0005643511,0.08288619,0.00004822018,0.00001398562,0.0001625506,0.0001191566,0.00008193225,0.007543506],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002922278,"threshold_uncertainty_score":0.008265138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01415983775985645,"score_gpt":0.2385919835471047,"score_spread":0.2244321457872482,"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."}}