{"id":"W4378365088","doi":"10.1109/tpwrs.2023.3280434","title":"EVSE Effectiveness in Multi-Unit Residential Buildings Using Composite Optimization and Heuristic Search","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Power Systems","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Heuristic; Schedule; Reliability engineering; Energy management; Operating cost; Operations research; Engineering; Energy (signal processing); Artificial intelligence","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":[0.0002086787,0.0001389084,0.0001810973,0.0004034694,0.000113844,0.00008054866,0.00006824853,0.0001061384,0.0000122024],"category_scores_gemma":[0.000001659972,0.0001481303,0.00003281247,0.0006202285,0.00002043708,0.0001477745,0.00000113551,0.0002565374,0.00001354058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001020134,"about_ca_system_score_gemma":0.00001330349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002745056,"about_ca_topic_score_gemma":0.00001467192,"domain_scores_codex":[0.9991316,0.00009521996,0.0002025012,0.0001797364,0.0001522232,0.0002387743],"domain_scores_gemma":[0.9996746,0.00009157821,0.00001679457,0.0001206111,0.0000369214,0.00005955771],"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":[0.00002391327,0.00001235831,0.0002259053,0.0001709748,0.00002725884,0.00001379029,0.0002231775,0.9747272,0.02444367,0.000005742161,0.00001128468,0.0001147621],"study_design_scores_gemma":[0.0006031499,0.00003656245,0.003087974,0.0001862119,0.0000154699,0.00003381621,0.00007263367,0.9881709,0.007618122,0.000001693153,0.00002016883,0.0001532748],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4406755,0.00006637548,0.5584142,0.000002256819,0.0004795032,0.0001964534,0.00001053616,0.000139254,0.00001593972],"genre_scores_gemma":[0.9993013,0.00004707325,0.0005319382,0.000002767496,0.000009245199,0.00002002191,0.000003002358,0.00003956723,0.00004514132],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5586258,"threshold_uncertainty_score":0.604058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01873274271821591,"score_gpt":0.2595084655496591,"score_spread":0.2407757228314432,"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."}}