{"id":"W4395025881","doi":"10.1016/j.apenergy.2024.123277","title":"An ecological input-output CGE model for unveiling CO2 emission metabolism under China's dual carbon goals","year":2024,"lang":"en","type":"article","venue":"Applied Energy","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"Natural Science Foundation of Fujian Province; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computable general equilibrium; Dual (grammatical number); China; Carbon fibers; Environmental science; Ecology; Economics; Natural resource economics; Biology; Computer science; Geography; Macroeconomics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005858316,0.001274214,0.0009516553,0.0006460531,0.0009867233,0.001429494,0.00154818,0.002378799,0.004064768],"category_scores_gemma":[0.001427781,0.0007464653,0.001023852,0.0008945956,0.0009278649,0.001280226,0.001016644,0.001182766,0.000270301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002455675,"about_ca_system_score_gemma":0.004021044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1321373,"about_ca_topic_score_gemma":0.07408397,"domain_scores_codex":[0.9998273,0.00004779323,0.000007591568,0.00005011439,0.00002517282,0.00004202055],"domain_scores_gemma":[0.999627,0.0001828771,0.00002556757,0.00002111802,0.00008953591,0.00005391348],"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":[0.00002195115,0.00001241876,0.0004604913,0.00001140392,0.00001030052,0.00003005525,0.000007999663,0.9977039,0.0001117555,0.0009389432,0.0001462225,0.0005446126],"study_design_scores_gemma":[0.00001392578,0.000004460892,0.0001626674,0.000001242747,0.000006126379,0.000001723308,0.000005897251,0.9992374,0.00004346911,0.0004285089,0.00009118058,0.000003458048],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7954826,0.0007397728,0.1504242,0.00304647,0.0003324787,0.0001761761,0.003843314,0.001257015,0.04469803],"genre_scores_gemma":[0.9898678,0.0001093404,0.005938594,0.00007717232,0.0000243753,0.00008233995,0.0004552939,0.0000647934,0.003380264],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1321373,"threshold_uncertainty_score":0.2627364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01200285267058687,"score_gpt":0.2501226372299217,"score_spread":0.2381197845593348,"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."}}