{"id":"W2890849782","doi":"10.1016/j.ijpe.2018.09.014","title":"Managing emissions allowances of electricity producers to maximize CO2 abatement: DEA models for analyzing emissions and allocating emissions allowances","year":2018,"lang":"en","type":"article","venue":"International Journal of Production Economics","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Inefficiency; Electricity; Data envelopment analysis; Environmental economics; Ecological efficiency; Electricity generation; Natural resource economics; Economics; Environmental science; Business; Microeconomics; Ecology; Power (physics); Engineering; Mathematics","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":[0.002266619,0.001442577,0.001693386,0.0008984001,0.0008411242,0.002851258,0.001568989,0.002771255,0.003041867],"category_scores_gemma":[0.005059924,0.001482226,0.001547635,0.001069594,0.0009017186,0.002442986,0.001220633,0.002320089,0.0002944458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003142849,"about_ca_system_score_gemma":0.002276087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02838071,"about_ca_topic_score_gemma":0.02318002,"domain_scores_codex":[0.9993873,0.0002944876,0.00002224662,0.00009723209,0.00007439787,0.0001243458],"domain_scores_gemma":[0.9977373,0.001647797,0.0002517854,0.00005989435,0.0001915503,0.0001117576],"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":[0.00001724817,0.00001672803,0.000132662,0.000009263068,0.00001137186,0.00001783136,0.000008177538,0.9961275,0.0001343156,0.002673301,0.00007483651,0.0007768875],"study_design_scores_gemma":[0.000006288218,0.00000682909,0.00005892136,0.000002459246,0.000007816437,0.000003004976,0.000007860677,0.997995,0.00009217707,0.001706086,0.000109961,0.0000036232],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3621563,0.001110377,0.6037799,0.002134819,0.0001623509,0.0002911826,0.0009817834,0.0002552624,0.02912808],"genre_scores_gemma":[0.9670104,0.0003716947,0.02255713,0.0001247446,0.00003591082,0.0001892146,0.0001785444,0.00007225076,0.009460018],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02838071,"threshold_uncertainty_score":0.05643106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0782257000300771,"score_gpt":0.3744225960859978,"score_spread":0.2961968960559206,"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."}}