{"id":"W2052878663","doi":"10.1016/j.jenvman.2006.04.028","title":"Future carbon balance of China's forests under climate change and increasing CO2","year":2006,"lang":"en","type":"article","venue":"Journal of Environmental Management","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":98,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Environmental science; Climate change; Carbon sink; Carbon sequestration; Primary production; Sink (geography); Ecosystem; Global warming; Atmospheric sciences; Carbon cycle; China; Global change; Carbon dioxide; Ecology; Geography","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":[0.0004267846,0.0004258728,0.0003440536,0.0007650866,0.0007817426,0.00101248,0.0004622578,0.0007991532,0.002835368],"category_scores_gemma":[0.0004129818,0.0002137783,0.0004419012,0.001054381,0.0004089801,0.001365343,0.0003596859,0.000297777,0.0001699604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00311698,"about_ca_system_score_gemma":0.002154253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06659722,"about_ca_topic_score_gemma":0.1205145,"domain_scores_codex":[0.9998813,0.00001246897,0.000008112777,0.00002284515,0.00002931998,0.000045927],"domain_scores_gemma":[0.9997486,0.0000241077,0.00005153002,0.00001119588,0.00009790624,0.00006658287],"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":[0.001290476,0.0002579994,0.7637797,0.0004432488,0.0007048877,0.002313785,0.001314302,0.08720601,0.04176188,0.02390393,0.01205907,0.06496467],"study_design_scores_gemma":[0.00009520088,0.0001371597,0.8895323,0.00002649256,0.0002598593,0.0002818144,0.0009388131,0.08736297,0.002691592,0.007914633,0.01068113,0.00007801998],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924167,0.0006831876,0.0004626334,0.001769333,0.000059107,0.000007453295,0.001248008,0.00003796813,0.003315481],"genre_scores_gemma":[0.9984115,0.0002401303,0.000168517,0.00008012322,0.00002366361,0.000005756819,0.0003757981,0.000005106479,0.0006894027],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06659722,"threshold_uncertainty_score":0.1324192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003891229808076038,"score_gpt":0.1726916221488128,"score_spread":0.1688003923407368,"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."}}