{"id":"W4385476856","doi":"10.1002/jssc.202300172","title":"High‐speed counter‐current chromatography assisted preparative isolation of phenolic compounds from the flowers of <i>Chrysanthemum morifolium</i> cv. Fubaiju","year":2023,"lang":"en","type":"article","venue":"Journal of Separation Science","topic":"Chromatography in Natural Products","field":"Chemistry","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Emergent BioSolutions (Canada)","funders":"Guangdong Provincial Pearl River Talents Program; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Chrysanthemum morifolium; Chlorogenic acid; Chemistry; Quinic acid; Chromatography; Vanillic acid; Acetic acid; Caffeic acid; Luteolin; Countercurrent chromatography; Phenolic acid; Flavonoid; High-performance liquid chromatography; Organic chemistry; Botany; Antioxidant","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":[0.0001632518,0.0008851244,0.0003917379,0.0006407052,0.0004412271,0.0003134476,0.0002416946,0.000324706,0.000965583],"category_scores_gemma":[0.0002276397,0.0001612731,0.0005305723,0.0003636093,0.0001923239,0.0002906193,0.0001587762,0.0004877097,0.0003163111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002721266,"about_ca_system_score_gemma":0.0002958615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002921985,"about_ca_topic_score_gemma":0.002878352,"domain_scores_codex":[0.9998949,0.00001744424,0.000006797766,0.00002882164,0.00002752247,0.00002457405],"domain_scores_gemma":[0.9999068,0.00002018999,0.00001510794,0.000008019665,0.00002815996,0.00002179096],"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":[0.00004465939,0.00001784749,0.0002468954,0.00004786956,0.00001226764,0.00005694635,0.00001573996,0.00002819371,0.997036,0.00002810719,0.00004089158,0.002424617],"study_design_scores_gemma":[0.00004942846,0.0003591444,0.03903042,0.00001688217,0.0000950543,0.0008315335,0.00005384312,0.001113993,0.9513168,0.0000839213,0.007020526,0.00002840942],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9611313,0.0073131,0.02600952,0.0002361479,0.0000807685,0.0002711425,0.001250464,0.0003691491,0.003338447],"genre_scores_gemma":[0.9425077,0.003043595,0.04481071,0.0003464842,0.00006586826,0.0002150558,0.003811683,0.0001203019,0.005078588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002921985,"threshold_uncertainty_score":0.005809963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02608334234651355,"score_gpt":0.3208492563630005,"score_spread":0.2947659140164869,"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."}}