{"id":"W3043435009","doi":"10.3390/electronics9071150","title":"Machine Learning Based PEVs Load Extraction and Analysis","year":2020,"lang":"en","type":"article","venue":"Electronics","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Artificial intelligence; Artificial neural network; Load profile; Energy (signal processing); Plug-in; Machine learning; Simulation; Engineering; Electricity; Mathematics; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005282267,0.00009952451,0.0001313374,0.00004810971,0.00005389432,0.0000294922,0.0000477926,0.00005887684,0.0001169693],"category_scores_gemma":[0.00001916522,0.00009988898,0.00005171981,0.0005353941,0.000006017164,0.00006762845,0.000006293541,0.0004120613,0.000006423497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008289615,"about_ca_system_score_gemma":0.00002827883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004006533,"about_ca_topic_score_gemma":0.00002037644,"domain_scores_codex":[0.9994376,0.00001354034,0.00009888049,0.0001250661,0.0001096204,0.0002152696],"domain_scores_gemma":[0.9998105,0.00001983997,0.00001986221,0.00006014531,0.00001888908,0.0000707982],"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":[0.0000392111,0.00001029431,0.01061468,0.00007373464,0.0005804558,0.000009177265,0.0003004197,0.8228599,0.04783104,0.0003404981,0.0009363399,0.1164042],"study_design_scores_gemma":[0.0001599773,0.00008672563,0.001747662,0.000001030744,0.0001232573,0.00000235125,0.000004523621,0.913444,0.004683451,0.00004142004,0.07959598,0.0001096499],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6679882,0.08291565,0.2412539,0.00161708,0.00009221573,0.0002230481,0.00001181301,0.001306767,0.004591264],"genre_scores_gemma":[0.9980723,0.001026957,0.0005883962,0.0001701945,0.00005705215,0.000001881019,0.00002332043,0.00001819819,0.00004170782],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.330084,"threshold_uncertainty_score":0.4073354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004081755142517517,"score_gpt":0.1934009450718803,"score_spread":0.1893191899293628,"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."}}