{"id":"W2324091296","doi":"10.1021/es3003684","title":"Black Carbon Emissions in China from 1949 to 2050","year":2012,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":313,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"National Development and Reform Commission; National Natural Science Foundation of China","keywords":"Carbon black; Environmental science; China; Greenhouse gas; Carbon fibers; Waste management; Environmental chemistry; Environmental protection; Chemistry; Engineering; Geography; Computer science; Geology; Oceanography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002180692,0.0004196665,0.0001659495,0.001152525,0.0004069855,0.0004015038,0.0001958926,0.0002381606,0.0008769459],"category_scores_gemma":[0.0002186038,0.0001371732,0.0003875798,0.001456786,0.0001457342,0.0003378358,0.0002664167,0.0001499069,0.0002162222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002064644,"about_ca_system_score_gemma":0.001229908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08696691,"about_ca_topic_score_gemma":0.1069229,"domain_scores_codex":[0.9998978,0.000006391741,0.000008342478,0.00002429635,0.00003696194,0.00002614348],"domain_scores_gemma":[0.9999096,0.000005677144,0.000021149,0.000005759082,0.00004556307,0.00001228619],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004215122,0.0001003989,0.8562579,0.000367948,0.0004380719,0.001495038,0.0005424287,0.02343164,0.01056533,0.0023777,0.009180153,0.09482197],"study_design_scores_gemma":[0.000009221602,0.00004758743,0.9734407,0.0000197389,0.00006271539,0.0001169646,0.00009067763,0.00341654,0.001900468,0.0002633694,0.02061286,0.00001913669],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9786456,0.002273644,0.0007525955,0.0004050976,0.00007797026,0.00002251982,0.01018927,0.00007310657,0.007560208],"genre_scores_gemma":[0.9852887,0.001331528,0.0009324143,0.0001600616,0.00002989502,0.00002709846,0.009083883,0.000009466047,0.00313696],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08696691,"threshold_uncertainty_score":0.1729214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004853488624925716,"score_gpt":0.1906545389585622,"score_spread":0.1858010503336365,"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."}}