{"id":"W2943595795","doi":"10.3390/en12091692","title":"A Multi-Objective Optimization Model for a Non-Traditional Energy System in Beijing under Climate Change Conditions","year":2019,"lang":"en","type":"article","venue":"Energies","topic":"Integrated Energy Systems Optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Renewable energy; Beijing; Climate change; Context (archaeology); Environmental science; Energy supply; Environmental economics; Electricity generation; Wind power; Natural resource economics; Environmental resource management; Power (physics); Energy (signal processing); Economics; China; Engineering; Geography; Mathematics; Statistics; Ecology","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":[0.00009885361,0.0002134188,0.0002420121,0.0003334138,0.00007891314,0.00004733774,0.00009738292,0.0001677021,0.00001266272],"category_scores_gemma":[0.000007103393,0.0002305807,0.00007079931,0.0002579585,0.00001741223,0.0004724578,0.00001547664,0.00008299779,0.000008522908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003958684,"about_ca_system_score_gemma":0.000027509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009819167,"about_ca_topic_score_gemma":0.0002191346,"domain_scores_codex":[0.9989833,0.00002522597,0.0003079672,0.000240385,0.00012681,0.0003163324],"domain_scores_gemma":[0.9995517,0.0000662512,0.00006165288,0.0001630706,0.0001177006,0.00003968137],"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":[0.000009800143,0.00002047006,0.0000521704,0.0001203907,0.00003217056,8.922585e-7,0.0003973518,0.9517842,0.0009925953,0.04651931,0.00005369535,0.0000169849],"study_design_scores_gemma":[0.0007646206,0.00001921685,0.0001306063,0.0002851392,0.00001364828,0.000005370216,0.0008342815,0.9971417,0.0004918523,0.00004625234,0.00001412331,0.0002531886],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04233716,0.0001035009,0.9524513,0.00001703115,0.000826664,0.0004668615,0.0002430511,0.000531273,0.003023144],"genre_scores_gemma":[0.9701738,0.00005318445,0.0276098,0.00004053799,0.0001201119,0.001105057,0.0006188406,0.00008109038,0.0001975664],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9278367,"threshold_uncertainty_score":0.9402809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0228664092006613,"score_gpt":0.2216250387439895,"score_spread":0.1987586295433282,"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."}}