{"id":"W4415820332","doi":"10.3390/wevj16110603","title":"EV and Renewable Energy Integration in Residential Buildings: A Global Perspective on Deep Learning, Strategies, and Challenges","year":2025,"lang":"en","type":"article","venue":"World Electric Vehicle Journal","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"Natural Resources Canada","keywords":"Renewable energy; Smart grid; Reinforcement learning; Cluster analysis; Energy management; Key (lock); Grid; Perspective (graphical); Electric vehicle","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":[],"consensus_categories":[],"category_scores_codex":[0.0002110101,0.0001990678,0.000224758,0.0004896485,0.0001704891,0.0002718953,0.0001086927,0.0001083266,0.00001612666],"category_scores_gemma":[0.00004267044,0.0001895248,0.0000367571,0.0009788669,0.00002331597,0.0003379839,0.00001705833,0.0006917159,4.754116e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006249554,"about_ca_system_score_gemma":0.00008132714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005636037,"about_ca_topic_score_gemma":0.004835531,"domain_scores_codex":[0.9988821,0.00008093025,0.0002624914,0.0002315637,0.0001676711,0.000375231],"domain_scores_gemma":[0.9996495,0.00005429203,0.00006012402,0.00007861656,0.00006977611,0.00008773625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003308676,0.00007953728,0.003961445,0.00008497116,0.0002262937,0.0001024375,0.0009960051,0.07333709,0.01770417,0.148914,0.004236631,0.7500265],"study_design_scores_gemma":[0.005735123,0.001702742,0.201053,0.000911782,0.0001777128,0.0008185929,0.006838842,0.4903983,0.01452013,0.2510419,0.0253457,0.001456068],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7330225,0.1871588,0.008206271,0.002667699,0.0004076825,0.0002208073,0.000001273007,0.0002680883,0.06804689],"genre_scores_gemma":[0.9819587,0.01736197,0.0001580095,0.00007387735,0.0001507253,0.000004894839,6.590834e-7,0.00001511045,0.0002760689],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7485704,"threshold_uncertainty_score":0.7728596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005428434371867661,"score_gpt":0.2230202039024847,"score_spread":0.217591769530617,"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."}}