{"id":"W2604384566","doi":"10.1088/1748-9326/aa6656","title":"Spatially explicit estimates of forest carbon emissions, mitigation costs and REDD+ opportunities in Indonesia","year":2017,"lang":"en","type":"article","venue":"Environmental Research Letters","topic":"Conservation, Biodiversity, and Resource Management","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"Australian Research Council; Skyrail Rainforest Foundation; California Institute of Technology; James Cook University; World Wildlife Fund","keywords":"Deforestation (computer science); Greenhouse gas; Environmental science; Logging; Carbon sequestration; Reducing emissions from deforestation and forest degradation; Natural resource economics; Palm oil; Climate change mitigation; Environmental protection; Agroforestry; Business; Climate change; Carbon stock; Forestry; Carbon dioxide; Geography; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005658831,0.0001104939,0.0001198347,0.0001097942,0.0004297562,0.00006411054,0.0003376225,0.00004768295,0.0001658556],"category_scores_gemma":[0.00006599735,0.0001076451,0.00002452867,0.00004407386,0.0009356579,0.0001974012,0.0008313154,0.0001503112,0.00001442345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002900938,"about_ca_system_score_gemma":0.000006272885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003229067,"about_ca_topic_score_gemma":0.0004323791,"domain_scores_codex":[0.9985574,0.00009570761,0.0001773339,0.0002773983,0.0006107005,0.0002813859],"domain_scores_gemma":[0.999339,0.00008962769,0.00009998743,0.0003545938,0.000002163008,0.0001146367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002655717,0.00005761968,0.9595941,0.00001322636,0.000006433941,0.00003266755,0.0004613663,0.00006626415,0.03271594,0.000006508847,0.0001631541,0.006856133],"study_design_scores_gemma":[0.0003819309,0.00004629127,0.9945858,0.0000432921,0.000005284196,0.000001339776,0.0009006176,0.0008312222,0.00247494,0.00006875799,0.0005543483,0.0001061454],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936425,0.00004320089,0.00001035909,0.00418054,0.00002316412,0.0003249971,0.000008624964,0.000006659943,0.001759952],"genre_scores_gemma":[0.9992264,0.0002339733,0.0001661135,0.0001370952,0.00001387108,0.00001872685,0.00001930209,0.000008477387,0.0001760765],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0349917,"threshold_uncertainty_score":0.4881405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04780131431725772,"score_gpt":0.2747689793275161,"score_spread":0.2269676650102584,"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."}}