{"id":"W2897130435","doi":"10.1016/j.ultsonch.2018.10.014","title":"Ultrasound-assisted extraction of bioactive compounds from green tea leaves and clarification with natural coagulants (chitosan and Moringa oleífera seeds)","year":2018,"lang":"en","type":"article","venue":"Ultrasonics Sonochemistry","topic":"Tea Polyphenols and Effects","field":"Medicine","cited_by":87,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"Fundação de Amparo à Pesquisa do Estado de Minas Gerais; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Gallic acid; Chemistry; Moringa; Chitosan; Chromatography; Extraction (chemistry); Polyphenol; Catechin; Epigallocatechin gallate; Centrifugation; High-performance liquid chromatography; Food science; Biochemistry; 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":[0.0001628212,0.0003956125,0.0002097795,0.0003273271,0.0002423435,0.0001677022,0.000138367,0.0002664118,0.000885483],"category_scores_gemma":[0.0001265547,0.0001615757,0.0003705008,0.0002204949,0.0001827633,0.0002562106,0.000188572,0.0003488197,0.0002188086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001761166,"about_ca_system_score_gemma":0.0002582328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001055938,"about_ca_topic_score_gemma":0.002610688,"domain_scores_codex":[0.9999263,0.000009055639,0.000006866878,0.00001562724,0.00002119469,0.00002082591],"domain_scores_gemma":[0.9999411,0.00001425277,0.00001269839,0.000006327051,0.00001401214,0.00001144785],"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":[0.00004994943,0.000006824027,0.0000609469,0.00002317963,0.000003639536,0.00001693876,0.00001309136,0.00001719317,0.9986703,0.00002026703,0.000008687223,0.001108794],"study_design_scores_gemma":[0.000004631966,0.00006605726,0.001503044,0.000002282892,0.00001721122,0.00004916478,0.00001277599,0.0002207044,0.9975834,0.00001188718,0.0005260517,0.000002776069],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989298,0.001898821,0.006998737,0.0000960592,0.00003326835,0.00004688731,0.0001121441,0.0000618784,0.001454092],"genre_scores_gemma":[0.9880706,0.001000126,0.006789566,0.00007947672,0.00001553738,0.0000330133,0.0001863185,0.00002511975,0.003800251],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001055938,"threshold_uncertainty_score":0.002962232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01129763215377852,"score_gpt":0.2584084187077826,"score_spread":0.2471107865540041,"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."}}