{"id":"W3047533158","doi":"10.29169/1927-5951.2020.10.04.6","title":"Ethics in Ethnobotanical Research: Intersection of Indigenous and Scientific Knowledge Systems","year":2020,"lang":"en","type":"article","venue":"Journal of Pharmacy and Nutrition Sciences","topic":"Indigenous Knowledge Systems and Agriculture","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ethnobotany; Traditional knowledge; Livelihood; Indigenous; State (computer science); Engineering ethics; Political science; Sociology; Geography; Traditional medicine; Engineering; Agriculture; Medicine; Ecology; Computer science; Medicinal plants","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.004267565,0.00007588111,0.0002163275,0.00007695064,0.0005608486,0.0001799589,0.0002080507,0.00007559314,0.00001115773],"category_scores_gemma":[0.0001910054,0.00002906092,0.00004569369,0.001130673,0.0004756636,0.0003235116,0.00005488894,0.0005218098,0.000001581185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002446933,"about_ca_system_score_gemma":0.00007212635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001585857,"about_ca_topic_score_gemma":0.0003121188,"domain_scores_codex":[0.9982682,0.0004596007,0.0004578431,0.0001886908,0.0004248689,0.0002008242],"domain_scores_gemma":[0.9986998,0.0004377089,0.0002169044,0.00001425479,0.0004902185,0.0001410811],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002594701,0.0006344648,0.01979844,0.0005537204,0.00001723956,0.00002532169,0.05070001,0.00001030657,0.9102106,0.0008643506,0.000857168,0.0160689],"study_design_scores_gemma":[0.008726344,0.01828643,0.1035067,0.006125765,0.0001275617,0.002039123,0.3222151,0.005681449,0.09306955,0.003909466,0.4347498,0.001562638],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9865695,0.01129557,0.000003775958,0.001479936,0.0003153303,0.0001990089,0.000009001727,0.000004550924,0.0001233915],"genre_scores_gemma":[0.9989239,0.0005797885,0.00002275531,0.00002072904,0.0004290795,0.000002830971,9.246709e-7,4.297698e-7,0.00001955145],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8171411,"threshold_uncertainty_score":0.431365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2607385164502219,"score_gpt":0.4049104155703299,"score_spread":0.144171899120108,"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."}}