{"id":"W4383955496","doi":"10.1002/fbe2.12057","title":"Bioactive peptides: Synthesis, applications, and associated challenges","year":2023,"lang":"en","type":"article","venue":"Food Bioengineering","topic":"Protein Hydrolysis and Bioactive Peptides","field":"Biochemistry, Genetics and Molecular Biology","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Exploit; Peptide; Computational biology; Amino acid; Combinatorial chemistry; Peptide synthesis; Fractionation; Biochemical engineering; Biotechnology; Biochemistry; Biology; Computer science; Chemistry; Engineering; Organic chemistry","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":[0.0001713105,0.0001477355,0.0001316581,0.00008950608,0.00007069832,0.00002233956,0.0001062545,0.0001169423,0.000002325041],"category_scores_gemma":[0.0001044744,0.0001404375,0.00005741812,0.0001738529,0.00004257104,0.000004956094,0.0001037506,0.00006110745,0.00001564763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001324404,"about_ca_system_score_gemma":0.00001112802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004051532,"about_ca_topic_score_gemma":0.00001331826,"domain_scores_codex":[0.9992294,0.00002085775,0.0001175356,0.0003156386,0.00008793512,0.0002285911],"domain_scores_gemma":[0.9996367,0.00002862931,0.000043685,0.0001897404,0.00003615811,0.0000651188],"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":[0.00001796537,0.00004954799,0.0005685835,0.00006802408,0.0003743874,0.000001653214,0.00005767586,0.0001341167,0.9694496,0.0004071592,0.0002107687,0.0286605],"study_design_scores_gemma":[0.0003378329,0.0004658006,0.02273518,0.00007248449,0.00005715635,0.000009880016,0.0004866321,0.0009741996,0.9386925,0.0001764331,0.03538746,0.0006044719],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9893543,0.007648276,0.001146653,0.0004378581,0.00005601361,0.0003903292,0.00009610216,0.0002066117,0.0006638393],"genre_scores_gemma":[0.9959367,0.003256057,0.0002294758,0.00001699344,0.0001346183,0.0002733146,0.00005777038,0.0000250277,0.00007006088],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03517669,"threshold_uncertainty_score":0.5726874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01723526953110257,"score_gpt":0.2289791257697144,"score_spread":0.2117438562386119,"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."}}