{"id":"W4392152408","doi":"10.1109/globecom54140.2023.10436949","title":"RLC: A Reinforcement Learning Based Charging Scheme for Battery Swap Stations","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Reinforcement learning; Swap (finance); Computer science; RLC circuit; Scheme (mathematics); Battery (electricity); Electrical engineering; Engineering; Voltage; Artificial intelligence; Capacitor; Business; Physics; Mathematics","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":[0.0007145883,0.0008733082,0.0008928758,0.0003360047,0.0004284124,0.0005273193,0.001779042,0.0009198245,0.003796302],"category_scores_gemma":[0.001962015,0.0002914487,0.0004118455,0.0003224466,0.0006129412,0.0008766711,0.001022135,0.001410272,0.0006362249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000845923,"about_ca_system_score_gemma":0.001166282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006399032,"about_ca_topic_score_gemma":0.006274128,"domain_scores_codex":[0.9996163,0.00008702905,0.00002391823,0.0000928607,0.00009688712,0.00008302929],"domain_scores_gemma":[0.9993591,0.0002231366,0.00008492359,0.00005808887,0.0001926081,0.00008213245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002510717,0.0002023034,0.001370001,0.00009582264,0.00004463844,0.000171277,0.00008127927,0.8491604,0.00462796,0.00696481,0.005198382,0.1318319],"study_design_scores_gemma":[0.00001408343,0.00003390524,0.0000639547,0.000003432439,0.00000425225,0.00001782599,0.000004566626,0.9977841,0.0004734217,0.001139938,0.0004556175,0.000004856171],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04111322,0.000552778,0.948922,0.000430617,0.0001762272,0.0001183945,0.0001157795,0.001856311,0.006714626],"genre_scores_gemma":[0.9387363,0.0001671983,0.05666143,0.0002842914,0.00003960752,0.0001165659,0.0001285908,0.0000831908,0.003782859],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006399032,"threshold_uncertainty_score":0.01272357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03520789372318988,"score_gpt":0.301426277255356,"score_spread":0.2662183835321661,"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."}}