{"id":"W2217989240","doi":"10.1139/cjfr-2015-0038","title":"Carbon storage, net primary production, and net ecosystem production in four major temperate forest types in northeastern China","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Forest ecology and management","field":"Environmental Science","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Program for Changjiang Scholars and Innovative Research Team in University; Fundamental Research Funds for the Central Universities; Ministry of Science and Technology of the People's Republic of China","keywords":"Larix gmelinii; Larch; Betula platyphylla; Primary production; Temperate rainforest; Forest ecology; Environmental science; Temperate forest; Ecosystem; Forestry; Temperate climate; Pinus koraiensis; Secondary forest; Carbon sequestration; Old-growth forest; Taiga; Litter; Agroforestry; Agronomy; Ecology; Botany; Biology; Geography; Carbon dioxide","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0004784179,0.0004441989,0.0002801156,0.001346978,0.0004723571,0.0004338293,0.0002883237,0.0002179651,0.0003588059],"category_scores_gemma":[0.000370482,0.0002417691,0.0003531767,0.001211926,0.0003566093,0.0004145087,0.0003537326,0.0000887082,0.00005056345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008672022,"about_ca_system_score_gemma":0.0004256005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04852297,"about_ca_topic_score_gemma":0.08918753,"domain_scores_codex":[0.9998261,0.00002184888,0.00002778965,0.0000533959,0.0000321098,0.00003877273],"domain_scores_gemma":[0.9996231,0.00005134892,0.0001268457,0.00003365104,0.00007676496,0.00008842192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006601334,0.00001709176,0.9916093,0.00002188512,0.00007214316,0.00009356162,0.0004530471,0.0004683849,0.004029685,0.00003874489,0.00004278186,0.003087341],"study_design_scores_gemma":[0.000001902632,0.000006609187,0.9994696,0.000001342829,0.000007885335,0.0000135917,0.00006937729,0.0003176407,0.00006639386,0.000008578196,0.00003513266,0.000001995232],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997322,0.00003638929,0.00003706417,0.000004067072,3.591019e-7,0.000001474011,0.0001097312,0.000001711419,0.00007701284],"genre_scores_gemma":[0.9994828,0.00003073141,0.00007873248,0.000005481088,9.713802e-7,0.000005790088,0.0002978184,8.605845e-7,0.00009689691],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04852297,"threshold_uncertainty_score":0.09648108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02227037276920251,"score_gpt":0.2466040762180006,"score_spread":0.2243337034487981,"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."}}