{"id":"W2510226494","doi":"10.1038/ngeo2798","title":"Global climate forcing of aerosols embodied in international trade","year":2016,"lang":"en","type":"article","venue":"Nature Geoscience","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":101,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Argonne National Laboratory; National Key Research and Development Program of China; Economic and Social Research Council; National Natural Science Foundation of China; Natural Environment Research Council; Sight Research UK; National Aeronautics and Space Administration","keywords":"Radiative forcing; Forcing (mathematics); Greenhouse gas; Aerosol; Environmental science; Atmospheric sciences; Sulfate aerosol; Climatology; Climate model; Cloud forcing; Climate change; Global warming; Goods and services; Radiative transfer; Geography; Meteorology; Economics; Economy; Oceanography; Physics","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":[0.0005256542,0.0003788305,0.0002458029,0.0004554288,0.0003450656,0.001159162,0.0003026483,0.001136434,0.00233438],"category_scores_gemma":[0.002187886,0.000302238,0.0006034479,0.0005433146,0.00042458,0.001267165,0.0006838728,0.000852871,0.0001873508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001344655,"about_ca_system_score_gemma":0.0008431311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01995551,"about_ca_topic_score_gemma":0.01435455,"domain_scores_codex":[0.999871,0.00003332065,0.00000909868,0.00002396499,0.00002888154,0.00003378965],"domain_scores_gemma":[0.9992835,0.0003719935,0.0001032374,0.00006985309,0.0001082616,0.00006316649],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0004399952,0.0002358275,0.1517713,0.0001904726,0.0003249498,0.001197856,0.0003865709,0.7194819,0.01488302,0.08903397,0.005039523,0.0170146],"study_design_scores_gemma":[0.0001032427,0.0001412368,0.2431915,0.0001290563,0.0002434177,0.0002368955,0.0007861681,0.6200788,0.006211595,0.1183346,0.01040049,0.0001431093],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9769215,0.0005895316,0.003350301,0.004043224,0.000265651,0.000008009153,0.0009453028,0.00005494915,0.01382154],"genre_scores_gemma":[0.9985726,0.0002757086,0.0001926812,0.00004934681,0.00003893961,0.000001797267,0.0001211575,0.00001324261,0.0007346328],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01995551,"threshold_uncertainty_score":0.03967875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01241123958122898,"score_gpt":0.2245078513562403,"score_spread":0.2120966117750114,"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."}}