{"id":"W4382983072","doi":"10.3390/jrfm16070317","title":"Using Carbon Tax to Reach the U.S.’s 2050 NDCs Goals—A CGE Model of Firms, Government, and Households","year":2023,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"World Bank Group","keywords":"Computable general equilibrium; Carbon tax; Economics; Greenhouse gas; Profit (economics); Government (linguistics); Natural resource economics; Agricultural economics; Macroeconomics; Microeconomics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006657137,0.0007256894,0.0006087338,0.0005309089,0.0009099239,0.002671188,0.001278715,0.002409425,0.006789887],"category_scores_gemma":[0.001344655,0.0003789243,0.0009408806,0.0006681061,0.001121499,0.003430872,0.001209406,0.001891938,0.0006770875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00399389,"about_ca_system_score_gemma":0.002835631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06697847,"about_ca_topic_score_gemma":0.04567396,"domain_scores_codex":[0.9996839,0.0001174448,0.000006355463,0.00005856589,0.00004409232,0.00008978009],"domain_scores_gemma":[0.9996777,0.000103657,0.0000502656,0.00002419351,0.00007270541,0.0000715194],"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":[0.00005355373,0.00006442328,0.001097757,0.00002645611,0.00001890874,0.0001336388,0.0001197359,0.5640823,0.0002958399,0.4266288,0.003716365,0.003762213],"study_design_scores_gemma":[0.00007566604,0.00006211695,0.0009384244,0.00003260647,0.00003055497,0.00006884959,0.0002599667,0.8173037,0.0001471049,0.170785,0.01025848,0.00003746151],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3577163,0.001599878,0.2115025,0.02410215,0.0004099823,0.0002532164,0.003005191,0.0003800427,0.4010307],"genre_scores_gemma":[0.9461221,0.0007136138,0.01115035,0.0005704447,0.00005577612,0.0001247545,0.0002738668,0.00005741684,0.04093162],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06697847,"threshold_uncertainty_score":0.1331772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08856246467227359,"score_gpt":0.2483360920317775,"score_spread":0.1597736273595039,"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."}}