{"id":"W2416440331","doi":"10.1109/les.2016.2578929","title":"Battery Current’s Fluctuations Removal in Hybrid Energy Storage System Based on Optimized Control of Supercapacitor Voltage","year":2016,"lang":"en","type":"article","venue":"IEEE Embedded Systems Letters","topic":"Electric and Hybrid Vehicle Technologies","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Ryerson University","keywords":"Supercapacitor; Computer science; Current (fluid); Energy storage; Voltage; Battery (electricity); Energy (signal processing); Electrical engineering; Capacitance; Electrode; Power (physics); Chemistry; Physics; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004197924,0.0003331467,0.0006492759,0.0006137118,0.00004677259,0.00003214996,0.0003547955,0.0001070934,0.000008546118],"category_scores_gemma":[0.00006392159,0.0002665602,0.0001458417,0.0002867987,0.00008868993,0.0001683607,0.000009550473,0.0002239271,0.00002526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000482336,"about_ca_system_score_gemma":0.00003488181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005754052,"about_ca_topic_score_gemma":0.000003420679,"domain_scores_codex":[0.9978858,0.0001768328,0.0007088584,0.000344767,0.0003805269,0.0005032039],"domain_scores_gemma":[0.9986486,0.0004925307,0.0001236081,0.0006044893,0.00005689868,0.0000738256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009418627,0.00006160053,0.0002451407,0.0005342306,0.0001070167,0.0002092657,0.00005789495,0.3564945,0.624216,0.0006402729,0.01399707,0.00334281],"study_design_scores_gemma":[0.004543141,0.00007972869,0.0001593223,0.001418176,0.00004769005,0.00004466181,0.00009262183,0.9487553,0.04303502,0.000006194505,0.001205182,0.0006129191],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4059374,0.0003593508,0.5899457,0.0001839205,0.002147868,0.0003540944,0.0001118977,0.0007921461,0.0001676738],"genre_scores_gemma":[0.9992359,0.0000189782,0.0001063055,0.00008429383,0.0002711001,0.0001739168,0.000006975643,0.00006683223,0.00003572295],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5932985,"threshold_uncertainty_score":0.9999787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008608014664521758,"score_gpt":0.1953323529317322,"score_spread":0.1867243382672105,"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."}}