{"id":"W1999908525","doi":"10.1021/pr049909x","title":"Definition and Characterization of a “Trypsinosome” from Specific Peptide Characteristics by Nano-HPLC−MS/MS and in Silico Analysis of Complex Protein Mixtures","year":2004,"lang":"en","type":"article","venue":"Journal of Proteome Research","topic":"Glycosylation and Glycoproteins Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Ottawa","funders":"","keywords":"In silico; Peptide; Chemistry; Characterization (materials science); High-performance liquid chromatography; Chromatography; Peptide mapping; Computational biology; Peptide sequence; Biology; Biochemistry; Nanotechnology; Materials science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001108653,0.0006449601,0.0007754276,0.0004968806,0.0002632481,0.000949416,0.0004673454,0.0005546433,0.0004204788],"category_scores_gemma":[0.001339652,0.0002801217,0.000583301,0.0004790035,0.0004603748,0.0005229189,0.0003168191,0.0008980587,0.0003594578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004826477,"about_ca_system_score_gemma":0.0004712269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007026199,"about_ca_topic_score_gemma":0.0006838197,"domain_scores_codex":[0.9994904,0.00009495563,0.00007146605,0.0001247227,0.0001785519,0.00003987902],"domain_scores_gemma":[0.9992496,0.0003204461,0.0001963216,0.00007379325,0.00009846933,0.00006125744],"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":[0.0001149264,0.00006462155,0.001845429,0.00007201584,0.00001410812,0.00006164778,0.00003269125,0.003645697,0.9907925,0.0002114817,0.00003896819,0.003105993],"study_design_scores_gemma":[0.00001210168,0.0001814853,0.008867528,0.00001014212,0.00002709127,0.0001863543,0.00003965836,0.07565014,0.9137727,0.000249255,0.0009825812,0.00002090999],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8092273,0.0005051958,0.1879488,0.0001032196,0.00002224481,0.0002934253,0.0009031461,0.0002740322,0.0007225878],"genre_scores_gemma":[0.8039724,0.0008635878,0.1911388,0.0001000006,0.00001176224,0.0004654528,0.002515254,0.0001351701,0.0007975553],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001108653,"threshold_uncertainty_score":0.00586313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04282690682207062,"score_gpt":0.3132530781847114,"score_spread":0.2704261713626408,"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."}}