{"id":"W3096528292","doi":"10.1007/s12231-020-09508-x","title":"Ethnicity Differences in Uses and Management Practices of Bitter Kola Trees (Garcinia kola) in Cameroon","year":2020,"lang":"en","type":"article","venue":"Economic Botany","topic":"African Botany and Ecology Studies","field":"Agricultural and Biological Sciences","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Agence Universitaire de la Francophonie; Agence Nationale de la Recherche; Agropolis Fondation","keywords":"Garcinia kola; Ethnic group; Geography; Overexploitation; Agroforestry; Felling; Threatened species; Ethnobotany; IUCN Red List; Ecology; Biodiversity; Biology; Forestry; Medicinal plants","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001510994,0.0001079948,0.0002767719,0.00001260082,0.00004768193,0.00001523344,0.0001403851,0.0000557838,0.0001399275],"category_scores_gemma":[0.00003659313,0.00004996695,0.00002882417,0.00009445805,0.0001200814,0.0001385446,0.0001312247,0.0000936202,0.00001405226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002456338,"about_ca_system_score_gemma":0.000003170318,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004902653,"about_ca_topic_score_gemma":0.02272548,"domain_scores_codex":[0.9991722,0.00007075723,0.0002595312,0.0002792687,0.00003679009,0.0001814891],"domain_scores_gemma":[0.9994653,0.000249153,0.000206244,0.00003128469,0.000004599665,0.00004335226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000885743,0.00004345411,0.9922296,0.000009355143,0.00002213401,0.000006787804,0.0004327197,0.000002496036,0.00214771,0.0000831359,0.0001698759,0.004764087],"study_design_scores_gemma":[0.0003053175,0.0001522268,0.9954815,0.00001275585,0.000008284764,6.444063e-7,0.002484306,0.0001002946,0.00004816324,0.00008920667,0.001214322,0.0001029709],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920008,0.0003762424,1.219785e-7,0.006312993,0.00004791645,0.000134827,0.0000114704,0.0000115667,0.001104051],"genre_scores_gemma":[0.9986538,0.000794329,0.00003559621,0.0003668582,0.00004928737,0.00001939465,6.742851e-7,6.578751e-7,0.00007939576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02223521,"threshold_uncertainty_score":0.9951072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05662350437880686,"score_gpt":0.2434492966640337,"score_spread":0.1868257922852268,"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."}}