{"id":"W3088180463","doi":"10.3390/membranes10100257","title":"Bovine Hemoglobin Enzymatic Hydrolysis by a New Ecoefficient Process—Part I: Feasibility of Electrodialysis with Bipolar Membrane and Production of Neokyotorphin (α137-141)","year":2020,"lang":"en","type":"article","venue":"Membranes","topic":"Protein Hydrolysis and Bioactive Peptides","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"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":"Hydrolysate; Electrodialysis; Chemistry; Enzymatic hydrolysis; Hydrolysis; Chromatography; Membrane; Membrane fouling; Salt (chemistry); Ultrafiltration (renal); Fouling; Biochemistry; Organic chemistry","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":[0.0003150153,0.0002546335,0.0005097893,0.00004974352,0.00005737364,0.00001596884,0.0001856415,0.0001082112,0.00003801218],"category_scores_gemma":[0.0002767189,0.000197512,0.0001219485,0.0004394278,0.0002432544,0.0000150137,0.00005881362,0.00008849203,0.000001154699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001862824,"about_ca_system_score_gemma":0.0001743699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001808469,"about_ca_topic_score_gemma":0.00009666571,"domain_scores_codex":[0.9982531,0.00009790703,0.0004322333,0.0006349559,0.0003499681,0.0002318266],"domain_scores_gemma":[0.9989306,0.00001370972,0.0003314274,0.0003686365,0.0002053334,0.000150339],"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":[0.0009404419,0.0002001539,0.00367483,0.0005764694,0.0002234712,6.567765e-7,0.0002302554,0.0003601809,0.9926595,0.000002856509,0.0002741196,0.0008570628],"study_design_scores_gemma":[0.0006980514,0.001079451,0.0002141916,0.00003473704,0.0002109346,0.000008987731,0.00008725939,0.0004447825,0.9952852,0.00001455179,0.001703512,0.0002183286],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928451,0.004938927,0.0002414948,0.0013322,0.0000201744,0.0005263141,0.00003279893,0.00001726161,0.00004568918],"genre_scores_gemma":[0.9987391,0.0003845308,0.0003247221,0.00009265111,0.0001377194,0.00002495947,0.00007916085,0.00002314074,0.0001940788],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005893898,"threshold_uncertainty_score":0.8054305,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01057562328324772,"score_gpt":0.2244751412592482,"score_spread":0.2138995179760005,"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."}}