{"id":"W2803329316","doi":"10.1038/s41598-018-26282-y","title":"Functional Proteomic Profiling of Secreted Serine Proteases in Health and Inflammatory Bowel Disease","year":2018,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Peptidase Inhibition and Analysis","field":"Medicine","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"CHIST-ERA; University of North Carolina at Chapel Hill; Région Occitanie Pyrénées-Méditerranée; Institut National de la Santé et de la Recherche Médicale; Conseil Régional Midi-Pyrénées; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fogarty International Center; Fundação de Amparo à Pesquisa do Estado de São Paulo; Agence Nationale de la Recherche","keywords":"Proteases; Cathepsin G; Serine; Protease; Kallikrein; Tryptase; Biology; Cathepsin; Cathepsin C; Proteolysis; Thrombin; MASP1; Biochemistry; Elastase; Serine protease; Enzyme; Immunology; Mast cell","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008236341,0.00008514882,0.0001744327,0.0002937876,0.0001141771,0.00002710524,0.00001798255,0.00002533457,0.0001696977],"category_scores_gemma":[0.0002987888,0.00007237296,0.00005432764,0.0003434098,0.0003508603,0.00009735647,0.000032261,0.00007459151,0.000005574354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004531298,"about_ca_system_score_gemma":0.0007256683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002506019,"about_ca_topic_score_gemma":0.00001261981,"domain_scores_codex":[0.9985184,0.00003831462,0.0005297335,0.0003986717,0.0003473253,0.00016753],"domain_scores_gemma":[0.9989045,0.00000576949,0.0002773284,0.0003202924,0.0001971218,0.0002950318],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003757705,0.0002743424,0.7626072,0.001496009,0.00003805823,0.0004964342,0.0003292056,0.00002324357,0.231905,0.00009830789,0.001691661,0.0006647624],"study_design_scores_gemma":[0.002183827,0.000460093,0.6414978,0.00520546,0.00007064945,0.0004540926,0.0005378593,0.00661527,0.3356502,0.00372893,0.003151802,0.0004440144],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983313,0.0001084701,0.00007430383,0.0004234724,0.0001603745,0.0007249484,0.000003985421,0.00003415454,0.0001389823],"genre_scores_gemma":[0.9979004,0.00000225693,0.0004911411,0.0000871892,0.00008098083,0.00005137097,0.0001180666,0.000007544332,0.001261106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1211094,"threshold_uncertainty_score":0.2951284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01586424460355981,"score_gpt":0.2686136878617197,"score_spread":0.25274944325816,"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."}}