{"id":"W4317809529","doi":"10.3390/en16031234","title":"Calibration of Grid Models for Analyzing Energy Policies","year":2023,"lang":"en","type":"article","venue":"Energies","topic":"Integrated Energy Systems Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Renewable energy; Grid; Marginal cost; Base load power plant; Electricity; Context (archaeology); Coal; Natural gas; Fossil fuel; Electricity pricing; Electricity generation; Environmental economics; Environmental science; Distributed generation; Economics; Engineering; Microeconomics; Electricity market; Power (physics); Waste management; Electrical engineering; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006638479,0.00009687176,0.0001406892,0.0002448122,0.00003665349,0.00001978559,0.00007829367,0.0000695401,0.000003712774],"category_scores_gemma":[0.00001534228,0.00009467104,0.00005306833,0.000416642,0.00001544514,0.0002250205,0.0000116352,0.00002305942,8.30531e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000276605,"about_ca_system_score_gemma":0.00001177849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003309893,"about_ca_topic_score_gemma":0.00009320458,"domain_scores_codex":[0.9994533,0.00001230838,0.0002124473,0.00008431744,0.00008072287,0.0001568973],"domain_scores_gemma":[0.9997113,0.00004891522,0.00003320988,0.0001240514,0.00006331891,0.00001924757],"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":[0.000002405661,0.000001618658,0.00001047451,0.00003430042,0.00002904757,1.941422e-7,0.0002562875,0.9261957,0.008954515,0.05982858,0.004399614,0.0002872151],"study_design_scores_gemma":[0.00007708117,0.000009920736,0.000009462767,0.00002270329,0.000007428865,4.011259e-7,0.0001538948,0.894298,0.1029091,0.001159506,0.001264144,0.00008834722],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1610682,0.0005996278,0.8286638,0.00008559268,0.001432788,0.0001138579,0.0000847851,0.001886289,0.006065066],"genre_scores_gemma":[0.99695,0.0001943499,0.001619108,0.0000088678,0.0001768491,0.00006315474,0.0001900213,0.00004050467,0.0007571155],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8358819,"threshold_uncertainty_score":0.3860573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01443451826835392,"score_gpt":0.2161089233103503,"score_spread":0.2016744050419964,"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."}}