{"id":"W4224925155","doi":"10.3389/fenrg.2022.773440","title":"Smart EV Charging Strategies Based on Charging Behavior","year":2022,"lang":"en","type":"article","venue":"Frontiers in Energy Research","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; University of Ottawa","keywords":"Software deployment; Idle; Scheduling (production processes); Load shifting; Smart grid; Electricity; Grid; Computer science; Peak demand; Demand response; Automotive engineering; Electric vehicle; Reliability engineering; Electrical engineering; Engineering; Power (physics); Operations management","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004106504,0.0006267244,0.0005332451,0.0004540118,0.0003051182,0.0007869495,0.0008529859,0.0003773079,0.001167578],"category_scores_gemma":[0.001335905,0.0002092098,0.0003038551,0.0003389798,0.0002958271,0.0008217135,0.0004831895,0.0002905401,0.0003438393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003935338,"about_ca_system_score_gemma":0.0004890062,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001159006,"about_ca_topic_score_gemma":0.001286305,"domain_scores_codex":[0.9996167,0.00007952919,0.00002701183,0.00007687194,0.0001134312,0.0000863138],"domain_scores_gemma":[0.9996763,0.00008435701,0.00006885359,0.00003776895,0.00009693574,0.0000357655],"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":[0.0003872106,0.0001477127,0.004516821,0.0001530671,0.00006798904,0.0002241858,0.0001811563,0.8239011,0.02535873,0.01493607,0.001810132,0.1283158],"study_design_scores_gemma":[0.00001411684,0.00007783709,0.0009906719,0.000008373288,0.00001879733,0.00009348764,0.00006524666,0.9905607,0.002796412,0.00418883,0.001170568,0.0000149667],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1852173,0.0006176629,0.7939869,0.0002707153,0.0001228462,0.0001491226,0.00008219514,0.0007088391,0.01884445],"genre_scores_gemma":[0.987491,0.0001470135,0.01102481,0.00004464978,0.00001413662,0.00002697272,0.00003542935,0.00002115603,0.001194795],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001167578,"threshold_uncertainty_score":0.003905892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01614806539424707,"score_gpt":0.2613958481259178,"score_spread":0.2452477827316707,"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."}}