{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002067174,0.0001598069,0.0002371052,0.00002701625,0.0001629311,0.00002367596,0.0004447984,0.00008823886,0.00001472768],"category_scores_gemma":[0.0001053187,0.0001154484,0.0001671683,0.0001208707,0.0001804829,0.000007584003,0.0003005379,0.0002252081,2.900742e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000170282,"about_ca_system_score_gemma":0.0001851154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004346215,"about_ca_topic_score_gemma":9.473875e-7,"domain_scores_codex":[0.9988344,0.00006485599,0.0004386776,0.0002268176,0.0002699663,0.0001652573],"domain_scores_gemma":[0.998809,0.00001378879,0.0005907284,0.0003673568,0.0001447015,0.00007444877],"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":[0.0000300337,0.000125065,0.001845423,0.00003618508,0.0001395448,0.000001260327,0.00006808218,0.00001504586,0.9944393,0.000009120486,0.002835054,0.0004558801],"study_design_scores_gemma":[0.0005509199,0.0001148004,0.004444554,0.00004455433,0.00007212272,0.00007876592,0.0003930754,0.000002125139,0.9705819,0.00004425742,0.02360233,0.00007059339],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9894329,0.009591217,0.00004038721,0.0002957797,0.0001637163,0.0001487898,0.0002028383,0.000003320888,0.0001210908],"genre_scores_gemma":[0.9983221,0.0008559529,0.0002293694,0.0001047733,0.0002881061,0.00001224832,0.00001197153,0.00001664308,0.0001588354],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02385741,"threshold_uncertainty_score":0.4707851,"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."}}