{"id":"W4312684622","doi":"10.1109/pesgm48719.2022.9917062","title":"Regionalisation in high share renewable energy system modelling","year":2022,"lang":"en","type":"article","venue":"2022 IEEE Power & Energy Society General Meeting (PESGM)","topic":"Integrated Energy Systems Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Electrification; Renewable energy; Environmental economics; Regionalisation; Electricity; Computer science; Energy carrier; Energy transition; Energy (signal processing); Cluster analysis; Greenhouse gas; Electricity generation; Business; Operations research; Power (physics); Economics; Engineering; Electrical engineering; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001048815,0.0006160009,0.000618708,0.0002994423,0.0006616319,0.000127137,0.0005838093,0.00035819,0.000294764],"category_scores_gemma":[0.00002274318,0.0007362387,0.000391664,0.00145946,0.00004329166,0.0003173755,0.0001583536,0.0005553309,0.00001192794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002255731,"about_ca_system_score_gemma":0.0001138729,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02039411,"about_ca_topic_score_gemma":0.002595742,"domain_scores_codex":[0.9956582,0.0005018023,0.00107866,0.0008490579,0.0009790044,0.0009333081],"domain_scores_gemma":[0.9985079,0.0001053552,0.0002887831,0.0007267339,0.0001977677,0.00017344],"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":[0.00001885981,0.00003895054,0.00005243798,0.00007005661,0.0001362057,0.000008775367,0.00117641,0.9356589,0.008295058,0.004490852,0.04999206,0.0000614508],"study_design_scores_gemma":[0.0005678188,0.00002712657,0.000002680072,0.0001486212,0.00003167427,0.00003690432,0.0009964681,0.8997008,0.002483793,0.0001661231,0.09508069,0.0007573366],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1829605,0.004303503,0.7797067,0.0003315545,0.01015235,0.0003825266,0.0002949836,0.002905023,0.01896288],"genre_scores_gemma":[0.964126,0.000260345,0.01651351,0.000422773,0.0007944903,0.0006882665,0.001829049,0.0003305963,0.01503496],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7811655,"threshold_uncertainty_score":0.9995089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01476313693641382,"score_gpt":0.1949568625944995,"score_spread":0.1801937256580857,"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."}}