{"id":"W2971414764","doi":"10.1049/iet-gtd.2019.0594","title":"Three‐based level model to determine optimal scheduling of the MG integrated operation using Benders decomposition","year":2019,"lang":"en","type":"article","venue":"IET Generation Transmission & Distribution","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Benders' decomposition; Scheduling (production processes); Decomposition; Mathematical optimization; Computer science; Reliability engineering; Mathematics; Engineering; Chemistry","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":[0.0001230048,0.0001794256,0.0001588345,0.00005925095,0.0001495764,0.00005066653,0.0001226655,0.0001511849,0.00006153205],"category_scores_gemma":[0.000006722539,0.0001432351,0.00009325622,0.0003324038,0.00001325462,0.0002227858,0.000008082444,0.0001708521,0.000003390594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002211241,"about_ca_system_score_gemma":0.00009775333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002238447,"about_ca_topic_score_gemma":0.00001632743,"domain_scores_codex":[0.9989679,0.00003016346,0.0003566064,0.0002059422,0.0002476773,0.0001916617],"domain_scores_gemma":[0.9995231,0.000009357371,0.00005675756,0.0001905081,0.0001456875,0.00007458436],"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":[0.00001416616,0.000008680109,0.00008071678,0.00001546519,0.000005489991,5.68606e-8,0.00002926728,0.5231706,0.4718518,0.00005642099,0.00007232519,0.004694982],"study_design_scores_gemma":[0.0002926647,0.00003170101,0.0004991106,0.00004251659,0.00001727847,0.000001695629,0.00000768436,0.6116284,0.3872966,0.00002424969,0.00005360853,0.0001045433],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4869944,0.00002798417,0.512445,0.00008590882,0.0000986788,0.0002247213,0.00007840517,0.00003841807,0.000006369718],"genre_scores_gemma":[0.9613647,0.000005325271,0.03770274,0.00006231145,0.00005457149,0.000009439545,0.0007725022,0.00002165996,0.000006765499],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4747423,"threshold_uncertainty_score":0.5840957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03357556815980629,"score_gpt":0.2536014061692364,"score_spread":0.2200258380094302,"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."}}