{"id":"W4391942881","doi":"10.1016/j.foodchem.2024.138777","title":"Identification, in silico selection, and mechanistic investigation of antioxidant peptides from corn gluten meal hydrolysate","year":2024,"lang":"en","type":"article","venue":"Food Chemistry","topic":"Protein Hydrolysis and Bioactive Peptides","field":"Biochemistry, Genetics and Molecular Biology","cited_by":55,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Shanghai Municipal Commission of Agriculture and Rural Affairs","keywords":"Antioxidant; Trolox; Chemistry; ABTS; Oxygen radical absorbance capacity; In silico; Corn gluten meal; Food science; Biochemistry; Tryptophan; Hydrolysate; Indole test; Amino acid; Antioxidant capacity; Organic chemistry; DPPH; Hydrolysis; Soybean meal","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":[0.0001641457,0.0001417997,0.0001490739,0.00003721752,0.00003788514,0.00004457886,0.0001072364,0.0001465033,0.00001565394],"category_scores_gemma":[0.00006662503,0.0001401952,0.00005504407,0.0001677628,0.00008561827,0.000009928739,0.00006002364,0.00009856011,0.000002470644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002108038,"about_ca_system_score_gemma":0.00006494546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006931257,"about_ca_topic_score_gemma":0.00006339682,"domain_scores_codex":[0.9989929,0.00002908332,0.000299234,0.0004217912,0.0001206949,0.0001362911],"domain_scores_gemma":[0.9995856,0.00001742253,0.00009129266,0.0001829943,0.00006793957,0.00005475815],"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":[0.00002537887,0.00001921589,0.003078053,0.0001136341,0.00008565617,0.000001163597,0.00005786629,0.00001361604,0.9961536,0.000033726,0.00007380146,0.0003442838],"study_design_scores_gemma":[0.0001663884,0.00007394993,0.004030618,0.00007778425,0.0000358604,0.00000879342,0.00004536191,0.001285974,0.9915732,0.002387132,0.0001672798,0.0001476205],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974817,0.001753188,0.0003650407,0.00007997666,0.00004329831,0.0001012966,0.00006613103,0.00002187761,0.00008749161],"genre_scores_gemma":[0.9991971,0.0001387748,0.0001887477,0.00001849317,0.0001341018,0.00003171835,0.0001538639,0.00001734271,0.0001198757],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004580367,"threshold_uncertainty_score":0.5716993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007241303282659713,"score_gpt":0.2156168210386662,"score_spread":0.2083755177560065,"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."}}