{"id":"W2374509577","doi":"","title":"Establishment of HPLC-fingerprint analysis for the quality assessment of Angelica sinensis","year":2003,"lang":"en","type":"article","venue":"","topic":"Traditional Chinese Medicine Analysis","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"CAE (Canada)","funders":"","keywords":"Angelica sinensis; Chromatography; High-performance liquid chromatography; Phosphoric acid; Chemistry; Fingerprint (computing); Quality assessment; Evaluation methods; Traditional Chinese medicine; Computer science; Medicine; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0004417738,0.000364109,0.0002594015,0.0006025327,0.0001561547,0.0002776906,0.0001658211,0.0002018665,0.0008301531],"category_scores_gemma":[0.0008330923,0.0001130915,0.0001568426,0.0002750081,0.000204603,0.0002674744,0.0001060798,0.0002884898,0.0003967385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002097485,"about_ca_system_score_gemma":0.0002626752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007714024,"about_ca_topic_score_gemma":0.001289787,"domain_scores_codex":[0.999751,0.00006171504,0.00001816328,0.00005471864,0.00009945661,0.00001488057],"domain_scores_gemma":[0.9996747,0.00006974542,0.00007530547,0.00003138517,0.0001161934,0.00003263998],"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":[0.00009396888,0.00003769429,0.002701557,0.00006402091,0.000007028154,0.0000293748,0.00001540259,0.00009690564,0.9828181,0.00003217762,0.00003068782,0.01407306],"study_design_scores_gemma":[0.00004275523,0.0008964172,0.03852128,0.0000225322,0.00005665185,0.0004941793,0.00003831648,0.003623123,0.9537714,0.00009677068,0.002421682,0.00001501684],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9052194,0.003831799,0.08642087,0.0002156546,0.00005883322,0.0002952144,0.001158979,0.0005255347,0.002273825],"genre_scores_gemma":[0.900518,0.001071893,0.09576958,0.00009962198,0.00003047253,0.0000924546,0.0008712725,0.00003297017,0.001513697],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.0008301531,"threshold_uncertainty_score":0.0027771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07508710055498138,"score_gpt":0.392039490670795,"score_spread":0.3169523901158137,"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."}}