{"id":"W1985483074","doi":"10.5402/2013/450948","title":"Simultaneous Extraction Optimization and Analysis of Flavonoids from the Flowers of <i>Tabernaemontana heyneana</i> by High Performance Liquid Chromatography Coupled to Diode Array Detector and Electron Spray Ionization/Mass Spectrometry","year":2012,"lang":"en","type":"article","venue":"ISRN Biotechnology","topic":"Natural product bioactivities and synthesis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Central Drug Research Institute","keywords":"Mass spectrometry; Chromatography; Extraction (chemistry); Chromatography detector; Detector; Analytical Chemistry (journal); Ionization; High-performance liquid chromatography; Materials science; Chemistry; Physics; Optics; Organic chemistry; Ion","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":[0.0001484594,0.0001647326,0.0002893706,0.0002004141,0.0000883502,0.00001046125,0.0001446047,0.0003212919,0.00001067452],"category_scores_gemma":[0.0001326368,0.0001324129,0.00006156994,0.000687997,0.0001818567,0.00001656106,0.00004567426,0.0001271871,3.292651e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002013215,"about_ca_system_score_gemma":0.00001253551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001960943,"about_ca_topic_score_gemma":0.0000798973,"domain_scores_codex":[0.999049,0.00004429867,0.0002456091,0.000304625,0.0001120545,0.0002444183],"domain_scores_gemma":[0.9992909,0.00007227567,0.000189535,0.0003373279,0.00006094601,0.00004905462],"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":[0.0001905458,0.00003847842,0.004130517,0.000008911011,0.0004276321,1.377173e-7,0.00002776069,0.001276197,0.9927133,0.00001140973,0.0000226794,0.001152477],"study_design_scores_gemma":[0.0001587236,0.0003713427,0.001799098,0.000005923551,0.0002809115,0.000003256295,0.00007601651,0.002101411,0.9947811,0.000002875746,0.0002701732,0.0001491571],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9524433,0.002686937,0.04399188,0.0005219321,0.00007295637,0.0001679813,0.0000900581,0.00001954161,0.000005384348],"genre_scores_gemma":[0.9919997,0.003229475,0.004491059,0.00006657024,0.00005637121,0.000006018292,0.0001233817,0.00001649109,0.00001086851],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03955644,"threshold_uncertainty_score":0.5399641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002589018396895749,"score_gpt":0.2011831992461192,"score_spread":0.1985941808492235,"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."}}