{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02677702,0.0006818313,0.0004290684,0.00105232,0.003754044,0.009900535,0.00311993,0.003104256,0.01799787],"category_scores_gemma":[0.03125734,0.0006380806,0.0008061393,0.003733065,0.003356554,0.0134677,0.007215115,0.00399892,0.003347847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005577484,"about_ca_system_score_gemma":0.006004304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01529899,"about_ca_topic_score_gemma":0.008848877,"domain_scores_codex":[0.9827084,0.008125592,0.0007071985,0.001953252,0.005104654,0.001401012],"domain_scores_gemma":[0.9811029,0.008447872,0.000739281,0.003375772,0.004870928,0.001463277],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004206602,0.001616693,0.03072352,0.0009775916,0.0001257604,0.002126923,0.03514662,0.0340003,0.006471877,0.2898974,0.02666826,0.5718244],"study_design_scores_gemma":[0.000162169,0.001113686,0.006346385,0.0009867643,0.00008862341,0.001307922,0.01244731,0.01306108,0.007148891,0.04711676,0.9100098,0.0002106604],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.3175108,0.006065678,0.0978412,0.01090003,0.001227463,0.001048219,0.0005158217,0.002065457,0.5628252],"genre_scores_gemma":[0.8333036,0.006940862,0.08101031,0.002762413,0.0003449078,0.0004404754,0.001735434,0.0006600748,0.07280186],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.02677702,"threshold_uncertainty_score":0.1416122,"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."}}