{"id":"W1995283805","doi":"10.1093/nar/gkr1025","title":"TopFIND 2.0--linking protein termini with proteolytic processing and modifications altering protein function","year":2011,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Michael Smith Health Research BC; Bundesministerium für Bildung und Forschung; Deutscher Akademischer Austauschdienst; Canadian Institutes of Health Research; Cancer Research Society; Alexander von Humboldt-Stiftung","keywords":"Biology; Proteome; Computational biology; Proteomics; Proteases; Protease; Cleavage (geology); Protein domain; UniProt; Biochemistry; Genetics; Gene; Enzyme","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":[0.0007516074,0.0001556901,0.0001162143,0.0001345785,0.0004006798,0.0001123691,0.0002467573,0.0001473168,0.00003010189],"category_scores_gemma":[0.0001480111,0.0001299349,0.00002220402,0.0002219725,0.0002655875,0.00002635003,0.0002268894,0.0004333074,0.00001892553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002559905,"about_ca_system_score_gemma":0.0001480453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002845603,"about_ca_topic_score_gemma":0.000009406142,"domain_scores_codex":[0.9985208,0.0001159644,0.0002272332,0.0003573823,0.0003637518,0.0004148568],"domain_scores_gemma":[0.9991512,0.000006230745,0.000092387,0.0004103433,0.0002296152,0.0001101804],"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":[0.0004231986,0.000108287,0.004300534,0.0005773161,0.0000387424,0.000005954127,0.001526193,0.00001437396,0.943268,0.0007892437,0.00003649818,0.04891163],"study_design_scores_gemma":[0.003642286,0.008649576,0.05051841,0.001951787,0.00006583167,0.0002542727,0.002719232,0.03345729,0.8726188,0.003819372,0.0204984,0.001804766],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.977584,0.00007500428,0.01285394,0.00009424504,0.00001045188,0.001321433,0.000002105771,0.00003925377,0.008019566],"genre_scores_gemma":[0.9746556,0.000003979727,0.02346893,0.00002225329,0.0000952531,0.0003827483,0.00001772923,0.00003945783,0.001314088],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07064925,"threshold_uncertainty_score":0.5298591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0479905212258674,"score_gpt":0.310058947810122,"score_spread":0.2620684265842546,"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."}}