{"id":"W4403118625","doi":"10.1016/j.clwas.2024.100172","title":"Influence of enzymatic hydrolysis conditions on antimicrobial activities and peptide profiles of milk protein-derived hydrolysates from white wastewater","year":2024,"lang":"en","type":"article","venue":"Cleaner Waste Systems","topic":"Protein Hydrolysis and Bioactive Peptides","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre in Green Chemistry and Catalysis; Agriculture and Agri-Food Canada; Parmalat (Canada); Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hydrolysate; Enzymatic hydrolysis; Antimicrobial; Hydrolysis; Peptide; Enzyme; Food science; Chemistry; Wastewater; Antimicrobial peptides; Milk protein; Biochemistry; Chromatography; Microbiology; Biology; Environmental science; Organic chemistry; Environmental engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003664347,0.0004836686,0.000365254,0.0002681966,0.0001221958,0.0006223103,0.0001279201,0.0003126972,0.0006900046],"category_scores_gemma":[0.0005911075,0.0001483058,0.0003482746,0.000404863,0.0002123171,0.0003592334,0.0002525412,0.0005210546,0.0003030913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001277376,"about_ca_system_score_gemma":0.0001856322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004752657,"about_ca_topic_score_gemma":0.0005641521,"domain_scores_codex":[0.9995871,0.00008074623,0.0000532807,0.00007316866,0.0001206122,0.00008506441],"domain_scores_gemma":[0.9997123,0.00009096962,0.00009175449,0.00001546353,0.00005672357,0.00003275369],"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":[0.0002107555,0.00003643499,0.0007698652,0.00007339673,0.00001047178,0.00006201378,0.00003816861,0.000103256,0.9968933,0.00001045315,0.00001239282,0.001779466],"study_design_scores_gemma":[0.000003730833,0.0004815512,0.01129323,0.00001595006,0.00002128261,0.00012511,0.0001430618,0.0004648844,0.9868177,0.0000179216,0.0006055873,0.000009910118],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973249,0.0009657746,0.000873532,0.00001980022,0.00000997582,0.00001639065,0.0002494781,0.00001085638,0.0005291559],"genre_scores_gemma":[0.995482,0.001061826,0.00187009,0.00004502789,0.000007770092,0.00004202603,0.0005980232,0.00001996161,0.0008734321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006900046,"threshold_uncertainty_score":0.002308309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006278906559811117,"score_gpt":0.2159445126543048,"score_spread":0.2096656060944937,"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."}}