{"id":"W2233487915","doi":"","title":"DNA barcoding in ethnobotany and ethnopharmacology : identifying medicinal plants traded in local markets","year":2015,"lang":"en","type":"article","venue":"Genome","topic":"Ethnobotanical and Medicinal Plants Studies","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ethnobotany; DNA barcoding; Biology; Medicinal plants; Evolutionary biology; Traditional medicine; Botany","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001418373,0.0001988179,0.0003307737,0.003464742,0.001077856,0.001459998,0.0006788374,0.0009138454,0.002681743],"category_scores_gemma":[0.004828521,0.0001768473,0.0002894491,0.006003024,0.001088015,0.001185568,0.001278675,0.0009671855,0.0005231717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007268857,"about_ca_system_score_gemma":0.001013059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006343927,"about_ca_topic_score_gemma":0.01470323,"domain_scores_codex":[0.9985722,0.000585489,0.00009082205,0.0003007305,0.0003482664,0.0001024465],"domain_scores_gemma":[0.9955988,0.001603033,0.001470497,0.000423131,0.0006653564,0.0002391127],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005697579,0.0002773544,0.2498267,0.002297985,0.000290001,0.00105124,0.01520465,0.0004992289,0.3214267,0.0179478,0.007522379,0.3830864],"study_design_scores_gemma":[0.00004686616,0.0002785362,0.6930732,0.001708377,0.000294051,0.002315356,0.03436591,0.004243542,0.08135479,0.01593925,0.1662717,0.0001084086],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9303683,0.007954044,0.02884316,0.005662983,0.0002742702,0.0002387482,0.008023043,0.0001054392,0.01853],"genre_scores_gemma":[0.920713,0.003041249,0.0618263,0.00181455,0.0001266233,0.0002343974,0.004504001,0.00006384334,0.007675974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006343927,"threshold_uncertainty_score":0.01261401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08671881422185683,"score_gpt":0.2933605510755658,"score_spread":0.206641736853709,"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."}}