{"id":"W2057714418","doi":"10.1515/bmc.2011.034","title":"On the cutting edge of proprotein convertase pharmacology: from molecular concepts to clinical applications","year":2011,"lang":"en","type":"article","venue":"BioMolecular Concepts","topic":"Protease and Inhibitor Mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Canadian Institutes of Health Research; National Institute of Diabetes and Digestive and Kidney Diseases; Ministère du Développement Économique, de l’Innovation et de l’Exportation","keywords":"Proprotein Convertases; Proteases; Context (archaeology); Lethality; Medicine; Disease; Bioinformatics; Proprotein convertase; Computational biology; Biology; Pathology; Toxicology; Internal medicine; Enzyme; Cholesterol; Biochemistry","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":[0.0003841048,0.000253117,0.0002631684,0.00004364034,0.0001028025,0.00001292854,0.0005557238,0.0002367547,0.0002473052],"category_scores_gemma":[0.0001707114,0.0002027437,0.0002363659,0.0001467208,0.00029468,0.000004624158,0.0002319432,0.0001691554,0.000136564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001293443,"about_ca_system_score_gemma":0.0001370346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006292385,"about_ca_topic_score_gemma":0.000002234291,"domain_scores_codex":[0.9979854,0.0003544639,0.0004885714,0.0006297873,0.0002190969,0.0003226359],"domain_scores_gemma":[0.9986224,0.00004351519,0.0002186096,0.000737581,0.0001707922,0.0002071473],"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":[0.0001642842,0.0001970421,0.000100895,0.000007536325,0.0001411372,0.0000201035,0.000106827,0.000001104092,0.9914204,0.003419801,0.00192649,0.002494369],"study_design_scores_gemma":[0.0007222247,0.0007286369,0.0000518939,0.00002947172,0.0000575261,0.000002799641,0.00007427848,0.00002117645,0.9837407,0.000941374,0.0133835,0.0002463778],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9095985,0.000957813,0.08410598,0.0002882726,0.0004102328,0.002454326,0.0001512785,0.00003813879,0.001995426],"genre_scores_gemma":[0.9920757,0.00001885221,0.002810955,0.004079814,0.0002836616,0.0005346494,0.00008943046,0.00003974902,0.000067141],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08247721,"threshold_uncertainty_score":0.8267649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0336222687953623,"score_gpt":0.3409024176907431,"score_spread":0.3072801488953808,"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."}}