{"id":"W2288641424","doi":"10.1002/wene.191","title":"Experience with linking greenhouse gas emissions trading systems","year":2015,"lang":"en","type":"article","venue":"Wiley Interdisciplinary Reviews Energy and Environment","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Inro Consultants (Canada)","funders":"World Bank Group","keywords":"Emissions trading; Greenhouse gas; Allowance (engineering); Clean Development Mechanism; Carbon offset; Business; Carbon leakage; European union; Kyoto Protocol; Directive; Offset (computer science); Environmental economics; Economics; Operations management; International trade; Computer science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0004153934,0.0002559759,0.0005739974,0.0001033033,0.0002101117,0.00007447533,0.0001967912,0.00009102851,0.0001439567],"category_scores_gemma":[0.000008709061,0.0002258642,0.00008416387,0.00006875043,0.0001208501,0.0002719512,0.0003485447,0.0001050223,0.0001261227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001807415,"about_ca_system_score_gemma":0.00000547897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008879388,"about_ca_topic_score_gemma":0.00002853596,"domain_scores_codex":[0.9984035,0.00002819023,0.0006954896,0.0005021297,0.00003588941,0.0003347846],"domain_scores_gemma":[0.9989368,0.00002429417,0.000327037,0.000411403,0.000002960976,0.0002975405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001043188,0.002731156,0.1973256,0.002253919,0.0008843568,0.0003716056,0.1983818,0.01444372,0.0003761491,0.3852295,0.04597167,0.1509874],"study_design_scores_gemma":[0.0008815372,0.0005434621,0.000387479,0.0009387835,0.0000284247,0.0001929916,0.002670097,0.01637239,0.00003451592,0.01150241,0.9655536,0.0008942884],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7110379,0.2102907,0.01942492,0.002568947,0.001403023,0.0008557845,0.0001885863,0.0001490008,0.0540811],"genre_scores_gemma":[0.9368089,0.06034762,0.0005772207,0.0002509136,0.0003215518,0.0002679429,0.00004656607,0.00004977723,0.001329488],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9195819,"threshold_uncertainty_score":0.9210474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1122519931325478,"score_gpt":0.2676970426520872,"score_spread":0.1554450495195393,"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."}}