{"id":"W3004818658","doi":"10.18387/polibotanica.49.15","title":"Adaptive co-management of urban forests: monitoring reforestation programs in Mexico City","year":2020,"lang":"en","type":"article","venue":"Polibotánica","topic":"Urban Green Space and Health","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Consejo Nacional de Ciencia y Tecnología; Australian Government","keywords":"Reforestation; Operationalization; Adaptive management; Forest management; Urban forest; Environmental planning; Urban forestry; Forestry; Environmental resource management; Urban planning; Distribution (mathematics); Citizen journalism; Afforestation; Geography; Business; Political science; Ecology; Environmental science","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":[0.0001310104,0.0001011571,0.0001496248,0.00002321328,0.00004086117,0.000008920629,0.0001962769,0.00004255573,0.00009100291],"category_scores_gemma":[0.000006369278,0.00009514437,0.00003838023,0.0003088861,0.00009576005,0.0001544934,0.0001176679,0.0001177114,0.00009178697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001802815,"about_ca_system_score_gemma":0.00001067355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001854136,"about_ca_topic_score_gemma":0.001239115,"domain_scores_codex":[0.9989161,0.00003398309,0.0002407281,0.0002449165,0.0002818514,0.0002824289],"domain_scores_gemma":[0.9995619,0.00001419183,0.0001056819,0.0001668574,0.000004527907,0.0001468642],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004758968,0.00006934189,0.9926931,0.00002665494,0.000008371211,0.000007135576,0.001647092,0.0001115559,0.0000534136,0.0005586151,0.0006631901,0.004113951],"study_design_scores_gemma":[0.0004027234,0.0002718983,0.9951071,0.00005534121,0.000009616951,3.145882e-7,0.0007324652,0.00085156,0.000340254,0.0003689391,0.001743012,0.0001167377],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9869007,0.00006563264,0.0003919779,0.001285117,0.00003851391,0.0005252034,0.000006555152,0.00005183051,0.01073447],"genre_scores_gemma":[0.9970729,0.00004906477,0.00256362,0.000111622,0.00004406919,0.00003290895,0.000006322082,0.00001209883,0.0001074107],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01062706,"threshold_uncertainty_score":0.3879875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07690254243038772,"score_gpt":0.2996571085906183,"score_spread":0.2227545661602306,"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."}}