{"id":"W3090196112","doi":"10.3390/membranes10100268","title":"Bovine Hemoglobin Enzymatic Hydrolysis by a New Eco-Efficient Process-Part II: Production of Bioactive Peptides","year":2020,"lang":"en","type":"article","venue":"Membranes","topic":"Protein Hydrolysis and Bioactive Peptides","field":"Biochemistry, Genetics and Molecular Biology","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Région Hauts-de-France; Agence Nationale de la Recherche; Université Laval","keywords":"Chemistry; Enzymatic hydrolysis; Hydrolysate; Hydrolysis; Hemoglobin; Antioxidant; Chromatography; Context (archaeology); Electrodialysis; Biochemistry; Membrane; Food science; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001939454,0.0002585994,0.000349908,0.00003989074,0.0001165346,0.00002021483,0.0002390119,0.0001322,0.00007331608],"category_scores_gemma":[0.0003681109,0.0002192934,0.0001726296,0.000312739,0.0001318291,0.00001095701,0.0001088351,0.0001006247,0.00001343861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002354394,"about_ca_system_score_gemma":0.0001606403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006675319,"about_ca_topic_score_gemma":0.0000155513,"domain_scores_codex":[0.9983783,0.00006512295,0.0003669747,0.0006051595,0.0003237752,0.0002606544],"domain_scores_gemma":[0.9991052,0.00001014074,0.0002535954,0.0003015372,0.0001712785,0.0001582612],"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":[0.0003398499,0.0002160563,0.0002404794,0.0002018323,0.0001719105,9.24589e-7,0.0005073448,0.0009397147,0.9907037,0.000004363077,0.005195417,0.0014784],"study_design_scores_gemma":[0.0004242817,0.000617085,0.00005605357,0.00003562735,0.00008423887,0.000006640627,0.0002420107,0.0007227084,0.983511,0.00002386901,0.01402288,0.0002535468],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943358,0.002245445,0.0001669981,0.002213122,0.00007829193,0.0004306849,0.00003618046,0.00003218984,0.0004613222],"genre_scores_gemma":[0.9975051,0.0001475004,0.0002251797,0.0002450994,0.0004082628,0.00004361335,0.00009792064,0.00002724551,0.001300118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008827467,"threshold_uncertainty_score":0.8942525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01037139747604058,"score_gpt":0.2287638448501373,"score_spread":0.2183924473740968,"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."}}