{"id":"W7116431507","doi":"10.1186/s40068-025-00414-6","title":"A high throughput ambient mass spectrometric approach for identifying the poaching of wild american ginseng","year":2025,"lang":"en","type":"article","venue":"ENVIRONMENTAL SYSTEMS RESEARCH","topic":"Ginseng Biological Effects and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; University of British Columbia","funders":"Environment and Climate Change Canada; Natural Sciences and Engineering Research Council of Canada; University of British Columbia","keywords":"Ginseng; Throughput; Poaching; Mass spectrometry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001037604,0.0001113947,0.0001789889,0.00009902539,0.0003091407,0.00004502988,0.0003574785,0.0000694603,0.000003445289],"category_scores_gemma":[0.00008139326,0.00007520527,0.00009681396,0.0003800293,0.0003921717,0.000002853331,0.0002145383,0.0001829353,0.000003697678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007580892,"about_ca_system_score_gemma":0.00001868305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003065827,"about_ca_topic_score_gemma":0.000001626281,"domain_scores_codex":[0.9985203,0.0002826393,0.0002223303,0.0003871074,0.0002604722,0.0003271374],"domain_scores_gemma":[0.999292,0.0001481314,0.00007933335,0.0004214936,0.00001488559,0.00004416923],"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":[0.00003732253,0.0001406885,0.002505925,0.00007125365,0.00007626709,2.757354e-7,0.0000238172,0.0005524136,0.9924868,0.001994772,0.0006084072,0.001502022],"study_design_scores_gemma":[0.002786728,0.002988207,0.1308536,0.000154907,0.0001064788,0.00002272258,0.01155989,0.00881855,0.7422268,0.0009712454,0.09860827,0.0009026239],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9284293,0.001356753,0.06782266,0.0001901017,0.00006837407,0.001324379,0.00005799024,0.000007682618,0.0007427702],"genre_scores_gemma":[0.9967889,0.000184458,0.001465807,0.00003049813,0.0001130981,0.0004422968,0.0001168389,0.00001235733,0.0008457672],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2502601,"threshold_uncertainty_score":0.3066782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03803850594625464,"score_gpt":0.3405249842502227,"score_spread":0.302486478303968,"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."}}