{"id":"W2092688496","doi":"10.1016/j.biortech.2009.01.073","title":"Characterization of enzymatic hydrolyzed snow crab (Chionoecetes opilio) by-product fractions: A source of high-valued biomolecules","year":2009,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Protein Hydrolysis and Bioactive Peptides","field":"Biochemistry, Genetics and Molecular Biology","cited_by":66,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; Université du Québec à Rimouski; Ministry of Agriculture, Fisheries and Food","funders":"Ministère de l'Agriculture et de l'Alimentation; Ministère de l'Agriculture, des Pêcheries et de l'Alimentation","keywords":"Chemistry; Hydrolysis; Polyunsaturated fatty acid; Chitin; Fractionation; Food science; Enzymatic hydrolysis; Amino acid; Chromatography; Snow; Dry weight; Fatty acid; Biochemistry; Biology; Botany","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":[0.000177842,0.0002540688,0.0004241024,0.000356924,0.00008010534,0.00001126155,0.0004094898,0.0003496585,0.00002318626],"category_scores_gemma":[0.0003174091,0.0002333947,0.0001383215,0.0005311529,0.0003632275,0.000008971902,0.0001097471,0.0001274207,0.000005999452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000015974,"about_ca_system_score_gemma":0.00003501521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005734991,"about_ca_topic_score_gemma":0.000005759141,"domain_scores_codex":[0.9984372,0.00008248044,0.0005155838,0.0005008401,0.0001792301,0.0002846376],"domain_scores_gemma":[0.9985567,0.00001330029,0.0005253013,0.000701156,0.0001535282,0.00005001646],"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":[0.00009621608,0.0002904987,0.001227115,0.00002208651,0.00009121577,5.700848e-7,0.00002016367,0.00000799519,0.9820282,0.0002374478,0.0001036801,0.01587479],"study_design_scores_gemma":[0.0005499754,0.0006334,0.003341571,0.00004865394,0.00005074868,0.00001231228,0.0000446362,0.00008849102,0.991285,0.0004827876,0.003234198,0.0002281968],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902284,0.001034223,0.007251273,0.0009083515,0.00003147215,0.0003691106,0.00005269404,0.00007411719,0.00005038782],"genre_scores_gemma":[0.9978169,0.0001595266,0.001370862,0.0001019833,0.00007058551,0.0000330927,0.000274922,0.00002418932,0.0001479376],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01564659,"threshold_uncertainty_score":0.951756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004795480530728327,"score_gpt":0.2184033727708763,"score_spread":0.213607892240148,"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."}}