{"id":"W4281563264","doi":"10.1111/jfbc.14249","title":"Antioxidative, anti‐inflammatory, and anticancer properties of the red biopigment extract from <i>Monascus purpureus</i> ( <scp>MTCC</scp> 369)","year":2022,"lang":"en","type":"article","venue":"Journal of Food Biochemistry","topic":"Microbial Metabolism and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Guru Angad Dev Veterinary and Animal Sciences University; Indian Council of Agricultural Research","keywords":"Chemistry; Monascus; Monascus purpureus; Antioxidant; Superoxide dismutase; Quercetin; ABTS; LNCaP; Glutathione peroxidase; Biochemistry; Food science; Molecular biology; Fermentation; Biology; DPPH; Cancer cell","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":[0.00009675481,0.0005272846,0.0002467696,0.0004738674,0.0001944145,0.0002090485,0.0001522535,0.0001967321,0.0006461546],"category_scores_gemma":[0.00007476762,0.00009052677,0.0003166941,0.0002942684,0.0001172149,0.000184088,0.0001359463,0.0003645011,0.0001303056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001174783,"about_ca_system_score_gemma":0.0001205935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004830079,"about_ca_topic_score_gemma":0.0007232309,"domain_scores_codex":[0.9999422,0.00001104106,0.000004363491,0.000008586157,0.00002106123,0.00001271925],"domain_scores_gemma":[0.9999305,0.000008644284,0.00002447466,0.000004151585,0.00001341893,0.00001876602],"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":[0.00007990091,0.00003379851,0.0001307519,0.00009366635,0.000008802584,0.00005221562,0.000007774678,0.00005951133,0.9976278,0.00002280462,0.00002318086,0.001859754],"study_design_scores_gemma":[0.00001316526,0.0007408392,0.008476503,0.00002520444,0.00007061906,0.0004267392,0.00004011381,0.0003923436,0.986249,0.00005472731,0.00349742,0.00001325308],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9877374,0.007955094,0.002234896,0.0001348597,0.00003598655,0.00003591663,0.000430947,0.00006268221,0.001372199],"genre_scores_gemma":[0.9937544,0.001674209,0.002284641,0.0001205735,0.0000242849,0.00001518945,0.0006016326,0.00001166832,0.001513412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006461546,"threshold_uncertainty_score":0.002161562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008038468194094517,"score_gpt":0.199999824521836,"score_spread":0.1919613563277415,"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."}}