{"id":"W2883416107","doi":"10.2200/s00850ed1v01y201804aat003","title":"Smart Charging and Anti-Idling Systems","year":2018,"lang":"en","type":"article","venue":"Synthesis lectures on advances in automotive technology","topic":"Electric and Hybrid Vehicle Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Automotive engineering; Engineering","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":[0.0001858784,0.0004659542,0.0004262221,0.000254458,0.000336475,0.001128913,0.0005061573,0.0005494459,0.008029651],"category_scores_gemma":[0.0004100589,0.0002092926,0.0002349279,0.0003865285,0.0005024687,0.001220015,0.000603188,0.0007811692,0.001625153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004766508,"about_ca_system_score_gemma":0.0001851971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002770229,"about_ca_topic_score_gemma":0.0002880138,"domain_scores_codex":[0.9998345,0.00002171725,0.000007219467,0.00004085125,0.00007194398,0.0000236402],"domain_scores_gemma":[0.9999062,0.00003086518,0.000006332994,0.0000200509,0.00002972224,0.00000695036],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003618083,0.00009018077,0.000344358,0.0004700496,0.00005437017,0.0001930221,0.0001455271,0.04436691,0.04189273,0.4959865,0.04009785,0.3759968],"study_design_scores_gemma":[0.00005606249,0.0003040086,0.0008797956,0.00008412535,0.0000563663,0.0006439653,0.0001056405,0.3213699,0.03576421,0.3532434,0.2874255,0.00006702697],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.03597918,0.01534852,0.7373285,0.00413448,0.00647082,0.00009406116,0.0002110406,0.001800511,0.1986329],"genre_scores_gemma":[0.7294046,0.008523923,0.05361015,0.001079101,0.001740086,0.00007790177,0.0002343299,0.0001966162,0.2051333],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.008029651,"threshold_uncertainty_score":0.02686185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005313175307836222,"score_gpt":0.2270298488439267,"score_spread":0.2217166735360905,"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."}}