{"id":"W3114608618","doi":"10.1101/2020.12.23.424126","title":"Are indigenous territories effective natural climate solutions? A neotropical analysis using matching methods and geographic discontinuity designs","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Conservation, Biodiversity, and Resource Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia; McGill University","funders":"Compute Canada","keywords":"Deforestation (computer science); Amazon rainforest; Indigenous; Amazon basin; Carbon stock; Spatial ecology; Climate change; Matching (statistics); Discontinuity (linguistics)","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.01551648,0.0003135758,0.0006120571,0.001265455,0.0009117906,0.001634108,0.001628688,0.0006098729,0.00561109],"category_scores_gemma":[0.03018666,0.0002270183,0.001479679,0.001699151,0.001231378,0.0007904164,0.002116841,0.0008463754,0.000195864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001172103,"about_ca_system_score_gemma":0.001283717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02690054,"about_ca_topic_score_gemma":0.01517798,"domain_scores_codex":[0.9865816,0.01027358,0.0003660538,0.001486668,0.0005939738,0.0006982835],"domain_scores_gemma":[0.9758974,0.01618091,0.00437519,0.002321897,0.0007333272,0.0004912596],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001075932,0.0003222438,0.9165231,0.0001885895,0.002734111,0.0003269143,0.002354608,0.006977658,0.0006576236,0.01581465,0.0008723973,0.05215212],"study_design_scores_gemma":[0.000162406,0.0007943766,0.8386199,0.000160332,0.001921183,0.0001799257,0.006720478,0.1310946,0.0007750238,0.01468462,0.004838788,0.00004843996],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9758557,0.000312163,0.02128114,0.0002903813,0.00001813842,0.0001415064,0.0003520218,0.00002372573,0.001725132],"genre_scores_gemma":[0.9951249,0.00003349502,0.004238908,0.00003291188,0.000005761155,0.0001019763,0.000116663,0.000005106539,0.0003403609],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02690054,"threshold_uncertainty_score":0.08205992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02396860798414127,"score_gpt":0.2549329111503496,"score_spread":0.2309643031662083,"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."}}