{"id":"W1898431817","doi":"10.2139/ssrn.2421136","title":"Reducing Emissions from Deforestation and Forest Degradation (REDD&amp;#43;), Transnational Conservation and Access to Land in Jambi, Indonesia","year":2013,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Conservation, Biodiversity, and Resource Management","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Bundesministerium für Wirtschaftliche Zusammenarbeit und Entwicklung; Ministry of Rural Affairs; Udenrigsministeriet; Universitetet i Oslo","keywords":"Deforestation (computer science); Reducing emissions from deforestation and forest degradation; Forest degradation; Land degradation; Nature Conservation; Environmental degradation; Agroforestry; Environmental protection; Business; Natural resource economics; Environmental science; Geography; Land use; Carbon stock; Climate change; Ecology; Economics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000215007,0.0001317354,0.00009148589,0.000151407,0.0006837568,0.0007180161,0.0003427572,0.0002629915,0.003617197],"category_scores_gemma":[0.0004174576,0.0001069286,0.0001111535,0.0003122244,0.0002390581,0.0004376739,0.000739084,0.0005607599,0.0001888437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009755647,"about_ca_system_score_gemma":0.00193212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05293303,"about_ca_topic_score_gemma":0.2068831,"domain_scores_codex":[0.9998914,0.0000258992,0.000008517844,0.00001277885,0.00001716641,0.00004433496],"domain_scores_gemma":[0.9998791,0.00001843462,0.00003421419,0.000004401167,0.00001528488,0.00004856477],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001159106,0.00115617,0.5117804,0.001081554,0.0001903772,0.00354575,0.0142828,0.004923561,0.01311458,0.01841275,0.01965168,0.4107012],"study_design_scores_gemma":[0.00003587296,0.0002240908,0.9460357,0.0001825174,0.0001185922,0.0006672592,0.01368598,0.00280669,0.002649821,0.001574911,0.03199498,0.00002360571],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.974096,0.0008626032,0.0002351426,0.002394191,0.00003835238,0.00002065374,0.0002932252,0.00001345669,0.02204647],"genre_scores_gemma":[0.987495,0.0007390237,0.0005142349,0.0002977225,0.000007795544,0.00002242494,0.0001172819,0.000006070805,0.01080041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05293303,"threshold_uncertainty_score":0.1052499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01352887210723612,"score_gpt":0.2234618004392516,"score_spread":0.2099329283320154,"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."}}