{"id":"W3125030099","doi":"10.1016/j.euroecorev.2020.103642","title":"Optimal carbon abatement in a stochastic equilibrium model with climate change","year":2020,"lang":"en","type":"article","venue":"European Economic Review","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":62,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"Deutsche Forschungsgemeinschaft","keywords":"Greenhouse gas; Economics; Climate change; Commit; Social cost; Externality; Marginal abatement cost; Kyoto Protocol; Microeconomics; Global warming; Econometrics; Elasticity of substitution; Natural resource economics; Environmental economics; Environmental science; Production (economics); Computer science; 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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008310105,0.0003430741,0.0009664352,0.0001269443,0.00003737236,0.00006997804,0.0004201511,0.00003971457,0.0003343005],"category_scores_gemma":[0.00003210764,0.0003820281,0.0001478992,0.0001230126,0.00005225991,0.0003338133,0.0002530075,0.0002079993,0.00329697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002328205,"about_ca_system_score_gemma":0.00001872391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007084334,"about_ca_topic_score_gemma":0.00003078932,"domain_scores_codex":[0.9973162,0.0000431838,0.001225101,0.0007746432,0.00002135189,0.0006194719],"domain_scores_gemma":[0.9987195,0.00002251536,0.00056339,0.0004483509,0.000007791762,0.0002385084],"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":[0.001299385,0.001183659,0.0426995,0.03275916,0.001069535,0.0005675791,0.02968745,0.579092,0.00006090946,0.2712262,0.01325302,0.02710165],"study_design_scores_gemma":[0.003190405,0.0005009636,0.002344091,0.002760563,0.0000926363,0.00003812862,0.0001196583,0.9565144,0.000007977446,0.0005964949,0.03174217,0.002092576],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5390316,0.1507857,0.001022358,0.03254696,0.0006647215,0.004349327,0.001609547,0.000358588,0.2696312],"genre_scores_gemma":[0.9022364,0.08125203,0.0007744429,0.01434781,0.0007255332,0.0002203859,0.00009537351,0.000233292,0.0001147065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3774224,"threshold_uncertainty_score":0.9998631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1786061425350924,"score_gpt":0.2704398291925948,"score_spread":0.09183368665750241,"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."}}