{"id":"W7127350814","doi":"10.1109/ccece64018.2025.11364446","title":"Enhancing EV Adoption: an Accurate State of Charge Prediction via Machine Learning","year":2025,"lang":"","type":"article","venue":"","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Automotive industry; Bridge (graph theory); Battery (electricity); State (computer science); State of charge; Range (aeronautics); TRIPS architecture","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":[0.0006991702,0.0006130601,0.000425077,0.0006124694,0.0001753301,0.0009255476,0.0008883186,0.0006589062,0.001162331],"category_scores_gemma":[0.003974827,0.0001754017,0.0004394209,0.000644479,0.0001672139,0.00119116,0.0005133278,0.000932305,0.0005929903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000511913,"about_ca_system_score_gemma":0.0004842583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01220523,"about_ca_topic_score_gemma":0.01766928,"domain_scores_codex":[0.9997194,0.00008311091,0.00002130627,0.00008383756,0.00005043605,0.00004182979],"domain_scores_gemma":[0.9988635,0.0006323485,0.0001316447,0.0001034703,0.0002339776,0.00003501895],"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":[0.0004205632,0.0009475253,0.1375995,0.0002275188,0.0001484349,0.0002456631,0.0002350307,0.6128986,0.00249794,0.003408857,0.007428502,0.2339419],"study_design_scores_gemma":[0.00000638602,0.00007595634,0.007801434,0.00001771762,0.00001579045,0.0000377069,0.00005962775,0.9882081,0.0007831915,0.001663309,0.00131882,0.00001198658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8002875,0.001034904,0.1817952,0.00181682,0.000132474,0.0001632907,0.003993366,0.00154199,0.009234344],"genre_scores_gemma":[0.9803488,0.0001731205,0.0163258,0.00008797666,0.00002627278,0.00004684179,0.001909704,0.00002223439,0.001059232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01220523,"threshold_uncertainty_score":0.02426839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004631874767725494,"score_gpt":0.2117520256084406,"score_spread":0.2071201508407151,"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."}}