{"id":"W2779887318","doi":"10.3390/molecules22122250","title":"Optimizing the Maximum Recovery of Dihydromyricetin from Chinese Vine Tea, Ampelopsis grossedentata, Using Response Surface Methodology","year":2017,"lang":"en","type":"article","venue":"Molecules","topic":"Medicinal plant effects and applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Priority Academic Program Development of Jiangsu Higher Education Institutions","keywords":"Response surface methodology; Box–Behnken design; Solvent; Extraction (chemistry); Chromatography; Chemistry; Materials science; Biochemistry","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":[0.0006540614,0.0003456342,0.0003671567,0.000274321,0.0001867368,0.0004372154,0.0002631001,0.000329456,0.0004262774],"category_scores_gemma":[0.0003663099,0.0001648572,0.0006581991,0.0002938969,0.0001520861,0.0003445568,0.0002756999,0.0003681916,0.0002334395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003190615,"about_ca_system_score_gemma":0.0003383023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005103187,"about_ca_topic_score_gemma":0.001436383,"domain_scores_codex":[0.9996542,0.0000821723,0.00002765829,0.00009315099,0.0001117829,0.00003113215],"domain_scores_gemma":[0.9999074,0.00003367561,0.00002562812,0.00001210831,0.00001593725,0.000005207085],"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":[0.00006139016,0.00004891421,0.0002185353,0.000151172,0.00001485358,0.00002161324,0.00001979012,0.000817791,0.9928524,0.00006151393,0.00002466366,0.005707406],"study_design_scores_gemma":[0.000006900784,0.0003174169,0.001917849,0.000007339187,0.0000235466,0.0000417238,0.00002381816,0.002556342,0.9938254,0.00006654757,0.001204339,0.000008707948],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.961121,0.001703143,0.03448056,0.0001131031,0.00002166463,0.0001748213,0.0004652628,0.0001292782,0.00179128],"genre_scores_gemma":[0.9482439,0.001104614,0.04771458,0.00006112742,0.000006458913,0.0001497438,0.0004011813,0.00003477591,0.00228375],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.0006540614,"threshold_uncertainty_score":0.003459036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06392903900092232,"score_gpt":0.364604358090046,"score_spread":0.3006753190891237,"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."}}