{"id":"W2768709594","doi":"10.1021/acs.analchem.7b02395","title":"Quantifying Missing (Phospho)Proteome Regions with the Broad-Specificity Protease Subtilisin","year":2017,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Jewish General Hospital","funders":"Ministerium für Innovation, Wissenschaft und Forschung des Landes Nordrhein-Westfalen; Bundesministerium für Bildung und Forschung; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Subtilisin; Proteome; Chemistry; Trypsin; Protease; In silico; Proteolysis; Peptide; Proteolytic enzymes; Biochemistry; Serine protease; Enzyme; Computational biology; Biology; Gene","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":[0.00101977,0.0005701032,0.0006473859,0.000633718,0.0002714961,0.0007476652,0.0003348665,0.0006735685,0.0008446223],"category_scores_gemma":[0.001092017,0.0004282411,0.0004000568,0.000672325,0.0003069045,0.0004268086,0.0005073011,0.0008852193,0.0004215494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002199895,"about_ca_system_score_gemma":0.0002081878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004096511,"about_ca_topic_score_gemma":0.0007629541,"domain_scores_codex":[0.9992305,0.0001023661,0.0000545696,0.0002689624,0.0002603869,0.00008327713],"domain_scores_gemma":[0.9992672,0.0002763536,0.0002060902,0.00008872903,0.00009382876,0.00006778345],"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":[0.0002228558,0.0000187518,0.002231326,0.0001663604,0.00004513475,0.00006805103,0.00003506126,0.0002132725,0.9942909,0.00003669874,0.00005273894,0.002618746],"study_design_scores_gemma":[0.00001282828,0.0003462322,0.04451002,0.00003018677,0.0001387702,0.0009928191,0.000103963,0.008805403,0.9420635,0.0002253879,0.002747717,0.00002323045],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9592348,0.003399263,0.03488036,0.00008148584,0.00004871309,0.00004042144,0.001405665,0.0003429982,0.0005662419],"genre_scores_gemma":[0.9462349,0.002841036,0.04581111,0.0001649169,0.00003081886,0.00009827721,0.003339913,0.0002018651,0.00127727],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00101977,"threshold_uncertainty_score":0.005393147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04711638891304788,"score_gpt":0.3174457207972944,"score_spread":0.2703293318842465,"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."}}