{"id":"W3027439832","doi":"10.1016/j.ocecoaman.2020.105241","title":"Opportunities for blue carbon strategies in China","year":2020,"lang":"en","type":"article","venue":"Ocean & Coastal Management","topic":"Coastal wetland ecosystem dynamics","field":"Environmental Science","cited_by":106,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Science and Technology Department of Zhejiang Province; State Oceanic Administration; Xiamen University; Ministry of Science and Technology of the People's Republic of China; Chinese Academy of Sciences","keywords":"Seagrass; Blue carbon; Habitat; Mangrove; Salt marsh; Environmental science; Eutrophication; Climate change; Ecology; Ecosystem; Resource (disambiguation); Marsh; Aquaculture; Wetland; Environmental protection; Fishery; Biology; Fish <Actinopterygii>","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":[0.0004264269,0.000302769,0.000190354,0.0007607279,0.00228844,0.001700084,0.0004457503,0.0006744264,0.003076972],"category_scores_gemma":[0.0002364273,0.0001006577,0.0002112101,0.001181788,0.0008890633,0.0007601666,0.001321908,0.0003879052,0.0000876687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005006399,"about_ca_system_score_gemma":0.01583352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.134192,"about_ca_topic_score_gemma":0.3053889,"domain_scores_codex":[0.9997138,0.00002808501,0.000007980813,0.00002854463,0.00003422236,0.0001873686],"domain_scores_gemma":[0.9997211,0.00001602694,0.0000240469,0.00001016491,0.00003969692,0.0001889625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004394951,0.0003540743,0.4003457,0.0006378646,0.0002606231,0.003522411,0.01750505,0.01124071,0.01810228,0.2453675,0.03442651,0.2677978],"study_design_scores_gemma":[0.0001128808,0.0002087977,0.7310459,0.0001738826,0.0001158722,0.0003423169,0.02370002,0.01456935,0.002310146,0.04030218,0.1870124,0.0001062854],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9506311,0.002490121,0.0006565718,0.009563077,0.00006176419,0.00002878213,0.0001610325,0.00003856712,0.03636892],"genre_scores_gemma":[0.9893529,0.0006160582,0.0003273012,0.0006051929,0.00001348432,0.0000147992,0.00006992356,0.00000405955,0.008996214],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.134192,"threshold_uncertainty_score":0.2668218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02115801702540867,"score_gpt":0.2108379468102308,"score_spread":0.1896799297848221,"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."}}