{"id":"W2618139994","doi":"10.1016/j.jclepro.2017.05.123","title":"Identifying optimal clean-production pattern for energy systems under uncertainty through introducing carbon emission trading and green certificate schemes","year":2017,"lang":"en","type":"article","venue":"Journal of Cleaner Production","topic":"Water resources management and optimization","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Light Source (Canada)","funders":"Higher Education Discipline Innovation Project","keywords":"Renewable energy; Environmental economics; Greenhouse gas; Electricity generation; Fossil fuel; Energy supply; Production (economics); Emissions trading; Environmental science; Computer science; Environmental engineering; Energy (signal processing); Engineering; Waste management; Power (physics); Economics; Mathematics; Microeconomics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001837074,0.0004903904,0.0008276275,0.0004497536,0.0003232965,0.001222033,0.0007516429,0.001278183,0.001671064],"category_scores_gemma":[0.00978006,0.0004824403,0.0005825903,0.0004832952,0.0006557888,0.001879264,0.0007297804,0.0009035544,0.00007388717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001005274,"about_ca_system_score_gemma":0.001576743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004379359,"about_ca_topic_score_gemma":0.003893813,"domain_scores_codex":[0.9995052,0.0002180203,0.00002485742,0.0001094281,0.00006686665,0.00007563591],"domain_scores_gemma":[0.9965179,0.002620123,0.0003910282,0.0001656893,0.0002140097,0.00009111949],"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":[0.00009706712,0.00005184937,0.001704822,0.00002712199,0.00002462851,0.00004030431,0.00001462908,0.9812409,0.0004336882,0.01003874,0.0001372969,0.006188957],"study_design_scores_gemma":[0.000008802408,0.00001761527,0.0003620955,0.000002653717,0.000007213012,0.000004706102,0.000007567619,0.9945149,0.0002402789,0.004777699,0.00005299644,0.000003443225],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5770295,0.0001961237,0.4166991,0.00092877,0.00003421621,0.0001001204,0.0002124198,0.0001242021,0.004675642],"genre_scores_gemma":[0.9892477,0.0000414622,0.01010716,0.00001752343,0.00000544799,0.00001403585,0.00004142947,0.00000678879,0.0005183662],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004379359,"threshold_uncertainty_score":0.009715497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05971306720566207,"score_gpt":0.2630076392189754,"score_spread":0.2032945720133134,"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."}}