{"id":"W7108478865","doi":"10.5287/ora-pdng5r1z7","title":"Jurisdictional approaches to reducing emissions from deforestation and forest degradation (REDD+) in Brazil","year":2022,"lang":"en","type":"dissertation","venue":"Oxford University Research Archive (ORA) (University of Oxford)","topic":"Environmental law and policy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Deforestation (computer science); Context (archaeology); Climate change; Greenhouse gas; Reducing emissions from deforestation and forest degradation; Climate change mitigation; Empirical research; Multidisciplinary approach","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.004058647,0.0001740665,0.0002408467,0.0009865998,0.002548356,0.002897072,0.0009609318,0.000672191,0.001226709],"category_scores_gemma":[0.004661077,0.00017345,0.000480161,0.001079092,0.004163778,0.001813952,0.003948796,0.0009300909,0.00005128244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007240842,"about_ca_system_score_gemma":0.01423321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05703221,"about_ca_topic_score_gemma":0.1524703,"domain_scores_codex":[0.9968991,0.001945222,0.0001022361,0.0002575251,0.0003705049,0.0004253697],"domain_scores_gemma":[0.9976313,0.001213722,0.000350498,0.000201161,0.0003658836,0.0002374152],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00006390021,0.000218508,0.05887858,0.001322429,0.00009559553,0.0009167746,0.1242629,0.006800702,0.004545333,0.6591581,0.002525056,0.1412121],"study_design_scores_gemma":[0.00006300551,0.0004526539,0.1767297,0.003573547,0.0003103213,0.001319118,0.3734211,0.01180644,0.004580974,0.1722405,0.25539,0.0001127471],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.7722583,0.007422981,0.0190635,0.01755107,0.000136494,0.0005389444,0.00016347,0.00005203073,0.1828132],"genre_scores_gemma":[0.992982,0.001268404,0.004255236,0.0004121483,0.000005143429,0.00007474007,0.00001356511,0.000003052867,0.0009858165],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05703221,"threshold_uncertainty_score":0.1134005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0529911825367901,"score_gpt":0.2965891352363074,"score_spread":0.2435979526995173,"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."}}