{"id":"W4297477901","doi":"10.3390/md20100610","title":"In Silico Analysis of Bioactive Peptides Produced from Underutilized Sea Cucumber By-Products—A Bioinformatics Approach","year":2022,"lang":"en","type":"article","venue":"Marine Drugs","topic":"Protein Hydrolysis and Bioactive Peptides","field":"Biochemistry, Genetics and Molecular Biology","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Scheme for Promotion of Academic and Research Collaboration; Hospital for Sick Children","keywords":"In silico; Computational biology; Sea cucumber; Functional food; Food products; Peptide; Chemistry; Biology; Biochemistry; Bioinformatics; Food science; Gene","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":[0.0004251025,0.0002392635,0.0004810695,0.0002672982,0.00009620104,0.00002099156,0.00036165,0.00008080176,0.0002054623],"category_scores_gemma":[0.00009666561,0.0002274518,0.0001899724,0.001246706,0.0001192268,0.00001491782,0.0007968647,0.0001894915,0.000002573448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006798428,"about_ca_system_score_gemma":0.00007751871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003796987,"about_ca_topic_score_gemma":0.0001422874,"domain_scores_codex":[0.9981769,0.000169089,0.0004694828,0.0005737054,0.0003257185,0.0002850874],"domain_scores_gemma":[0.9988852,0.00002615657,0.0002788786,0.0006658437,0.00008783121,0.00005613833],"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":[0.0006132754,0.00100267,0.08479102,0.00005573813,0.002469269,0.000001946643,0.0008171029,0.001401132,0.9015465,0.00004035644,0.00267974,0.004581243],"study_design_scores_gemma":[0.001547291,0.0002896638,0.009479047,0.000003977707,0.0006438291,0.000002094228,0.002246058,0.01671252,0.9578035,0.000157212,0.01053241,0.0005823398],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995203,0.0002405371,0.0001440206,0.0002462827,0.00004910798,0.0003948824,0.0004194542,0.00001256484,0.003290175],"genre_scores_gemma":[0.9938393,0.00005410305,0.001658985,0.0001870262,0.0000553292,0.0001390992,0.003167823,0.00002127223,0.0008770546],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07531197,"threshold_uncertainty_score":0.9275215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007418546724173854,"score_gpt":0.2287707125619754,"score_spread":0.2213521658378015,"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."}}