{"id":"W2064941693","doi":"10.1016/j.foodres.2012.07.048","title":"DNA barcodes for everyday life: Routine authentication of Natural Health Products","year":2012,"lang":"en","type":"article","venue":"Food Research International","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":152,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Government of Canada; U.S. Food and Drug Administration; Ontario Genomics Institute; Genome Canada","keywords":"DNA barcoding; Barcode; Ginseng; Biology; Authentication (law); Computational biology; Mitochondrial DNA; DNA; Evolutionary biology; Gene; Genetics; Business; Medicine; Computer science; Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001430039,0.0008931809,0.0005713367,0.001673467,0.0008450127,0.001141789,0.001021287,0.001779126,0.004015203],"category_scores_gemma":[0.003938867,0.0003754782,0.0003201426,0.001096855,0.001292696,0.001243662,0.001170845,0.001499937,0.004429055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004674452,"about_ca_system_score_gemma":0.001566261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009767272,"about_ca_topic_score_gemma":0.001886302,"domain_scores_codex":[0.9980758,0.0004519981,0.00009241772,0.0003514069,0.0008823755,0.0001459499],"domain_scores_gemma":[0.9974052,0.0006029325,0.0005040778,0.0003256851,0.0009036479,0.0002583201],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004368364,0.0001572668,0.008987906,0.0007251306,0.00003443102,0.0001359337,0.0005855979,0.00015059,0.7501261,0.002469441,0.005155584,0.2310352],"study_design_scores_gemma":[0.00001827465,0.0005387957,0.01079143,0.0002544622,0.00005822152,0.001099834,0.0004639043,0.001677735,0.9257397,0.001971209,0.05731782,0.00006847263],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3699166,0.04499918,0.5251566,0.007145603,0.002850936,0.001167869,0.00925604,0.005463582,0.03404365],"genre_scores_gemma":[0.5029813,0.01965362,0.4300455,0.002738515,0.0003641444,0.0008681595,0.00581523,0.0005575898,0.03697586],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004015203,"threshold_uncertainty_score":0.0134322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1314828836264735,"score_gpt":0.4294770980917296,"score_spread":0.2979942144652562,"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."}}