{"id":"W6920753011","doi":"10.6084/m9.figshare.19906081.v1","title":"Additional file 6 of Stand carbon storage and net primary production in China’s subtropical secondary forests are predicted to increase by 2060","year":2022,"lang":"en","type":"article","venue":"Figshare","topic":"Forest, Soil, and Plant Ecology in China","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Primary production; Subtropics; Biomass (ecology); Production (economics); Tropical and subtropical moist broadleaf forests; Diameter at breast height","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007263421,0.0008573744,0.0009012084,0.001863647,0.0003592003,0.0007901822,0.001458636,0.0006060625,0.5514841],"category_scores_gemma":[0.0050902,0.0004254038,0.0007334939,0.005518967,0.0001166005,0.001316815,0.0006403213,0.000536476,0.06600294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007611967,"about_ca_system_score_gemma":0.00159121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03129794,"about_ca_topic_score_gemma":0.03112479,"domain_scores_codex":[0.9996433,0.00003741961,0.00006587639,0.00009410573,0.00007075172,0.00008847534],"domain_scores_gemma":[0.9974397,0.001086236,0.0003637372,0.0001994279,0.000759853,0.0001510982],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001453528,0.00006229386,0.01498816,0.001967807,0.0001005404,0.00008140737,0.00006561046,0.001430201,0.0001193212,0.0008323504,0.9702224,0.009984494],"study_design_scores_gemma":[0.002901779,0.0001497651,0.2005507,0.001827988,0.0003240385,0.0002464196,0.0006954575,0.008273243,0.0008593034,0.005978168,0.7780174,0.0001757518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002398244,0.000009357378,0.00005410512,0.00002435722,0.000005710453,0.0000110204,0.9992864,0.00007291939,0.0002963038],"genre_scores_gemma":[0.01030296,0.00006788452,0.0006938264,0.00009887326,0.00002809457,0.0003799341,0.985581,0.0001233662,0.002724102],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5514841,"threshold_uncertainty_score":0.6397535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00953268242402403,"score_gpt":0.2187929559370833,"score_spread":0.2092602735130593,"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."}}