{"id":"W2137513220","doi":"10.1186/1749-8546-5-14","title":"Quantitative analysis of two isoflavones in Pueraria lobata flowers from eleven Chinese provinces using high performance liquid chromatography","year":2010,"lang":"en","type":"article","venue":"Chinese Medicine","topic":"Phytoestrogen effects and research","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Sun Yat-sen University","keywords":"Pueraria; Chemistry; High-performance liquid chromatography; Chromatography; Lobata; Angelica sinensis; Isoflavones; Herb; Traditional medicine; Traditional Chinese medicine; Biochemistry; Medicine; Medicinal herbs","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008263041,0.0003886192,0.001464334,0.001555032,0.00009489214,0.00001197458,0.0003357517,0.0001403176,0.0003850406],"category_scores_gemma":[0.0007697314,0.0002211994,0.0002183645,0.004255351,0.0006662337,0.000236769,0.0001087461,0.0006703756,0.000005476593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004415721,"about_ca_system_score_gemma":0.0002059444,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007503272,"about_ca_topic_score_gemma":0.002512255,"domain_scores_codex":[0.9974196,0.0001164943,0.0007045348,0.0005406404,0.0007722453,0.0004464767],"domain_scores_gemma":[0.9980599,0.0004757181,0.0002520386,0.0007058563,0.0002448944,0.0002616474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009288115,0.0002789356,0.5792544,0.0001572986,0.0009190931,0.00006905273,0.0009212852,0.0002078128,0.4167197,0.00005363788,0.00001700422,0.0004729958],"study_design_scores_gemma":[0.003871009,0.00179889,0.8948439,0.0004284284,0.0009294763,0.00001614045,0.0001616756,0.09330074,0.004155568,0.0002288413,0.00001562716,0.0002496884],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969199,0.0008318439,0.0001457308,0.0005894543,0.000504297,0.0005946059,0.00006065231,0.00004572488,0.0003077712],"genre_scores_gemma":[0.9972274,0.0001204456,0.001728539,0.00009221601,0.0004852974,0.00002126693,0.0002666382,0.00003610995,0.00002211703],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4125641,"threshold_uncertainty_score":0.9991059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01672961026379943,"score_gpt":0.3470039432929685,"score_spread":0.3302743330291691,"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."}}