{"id":"W2935686593","doi":"10.1016/j.forpol.2019.04.004","title":"Assessing the potential of community-based forestry programs in Panama","year":2019,"lang":"en","type":"article","venue":"Forest Policy and Economics","topic":"Conservation, Biodiversity, and Resource Management","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Smithsonian Tropical Research Institute; Vedecká Grantová Agentúra MŠVVaŠ SR a SAV; Social Sciences and Humanities Research Council of Canada; McGill University","keywords":"Sustainability; Panama; Business; Government (linguistics); Agriculture; Poverty; Environmental resource management; Resource (disambiguation); Community forestry; Environmental planning; Forest management; Forestry; Natural resource economics; Economic growth; Geography; Economics; Ecology; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002431424,0.00005772586,0.00007624491,0.00003587937,0.0001365588,0.00005372282,0.0001721627,0.00003491393,0.00003607269],"category_scores_gemma":[0.000006076733,0.00004602004,0.00002921045,0.00007064065,0.0001720678,0.0001111992,0.000208721,0.00008732064,0.00002098305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005532596,"about_ca_system_score_gemma":0.00001269409,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007651464,"about_ca_topic_score_gemma":0.002421167,"domain_scores_codex":[0.9996122,0.00004242282,0.0001164599,0.00006935767,0.00003409081,0.0001255424],"domain_scores_gemma":[0.9996937,0.00003492379,0.00006651295,0.0001779442,0.000001888361,0.0000250361],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000005769864,0.00004119656,0.9816679,0.00001752218,0.000004203018,1.815335e-7,0.0003831613,0.01382244,0.000008979714,0.0002367862,0.00001637372,0.003795441],"study_design_scores_gemma":[0.0002952721,0.00003258447,0.9822816,0.000006529629,0.000005230987,5.807925e-7,0.001138157,0.009434562,0.000006747521,0.001353862,0.005389449,0.00005541099],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954224,0.000003050956,0.00002023069,0.0009710339,0.00002868542,0.0001601245,0.000002900004,0.000005382008,0.003386168],"genre_scores_gemma":[0.9992497,0.000008746582,0.00007605122,0.0005101913,0.00001696053,0.000002503996,0.00001346436,0.000003208239,0.0001191881],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005373075,"threshold_uncertainty_score":0.9989567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03059235579303106,"score_gpt":0.2337586011513543,"score_spread":0.2031662453583232,"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."}}