{"id":"W2162918649","doi":"10.1074/mcp.m700264-mcp200","title":"Quantitative Profiling of Ubiquitylated Proteins Reveals Proteasome Substrates and the Substrate Repertoire Influenced by the Rpn10 Receptor Pathway","year":2007,"lang":"en","type":"article","venue":"Molecular & Cellular Proteomics","topic":"Ubiquitin and proteasome pathways","field":"Biochemistry, Genetics and Molecular Biology","cited_by":96,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"National Center for Research Resources; National Institutes of Health; Michael Smith Health Research BC; Howard Hughes Medical Institute","keywords":"Ubiquitin; Repertoire; Ubiquitin-Protein Ligases; Proteasome; Receptor; Cell biology; Profiling (computer programming); Chemistry; Computational biology; Biology; Ubiquitin ligase; Biochemistry; Computer science; Gene","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003185463,0.000458149,0.0004494381,0.00006294548,0.0003697363,0.00009976825,0.0006237663,0.0003855611,0.00001044793],"category_scores_gemma":[0.000579442,0.0003010264,0.0002241222,0.0003428829,0.0008706211,0.00001879844,0.0002389262,0.0004962515,0.000006625689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002781027,"about_ca_system_score_gemma":0.0001851048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008877803,"about_ca_topic_score_gemma":0.0000181512,"domain_scores_codex":[0.9968149,0.0005965372,0.0008282824,0.0007074709,0.000416737,0.0006360785],"domain_scores_gemma":[0.9979437,0.00008247684,0.0005977926,0.0008704158,0.0003547147,0.0001509244],"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":[0.001089486,0.00007470699,0.0003526474,0.0001256608,0.0001372442,0.00001223136,0.0003890655,0.00002274573,0.9922002,0.005167807,0.00002448587,0.0004036946],"study_design_scores_gemma":[0.001569354,0.0005355313,0.00007490751,0.00008537417,0.00004102616,0.00002553038,0.0004285991,0.0001181093,0.9949433,0.001309694,0.0004754409,0.0003931293],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.981491,0.004443773,0.007572153,0.0004343324,0.00006653486,0.005454541,0.00008751712,0.00003658611,0.0004135658],"genre_scores_gemma":[0.9901222,0.000120435,0.008404332,0.0002500525,0.00006810403,0.0005283157,0.0001936863,0.0000779227,0.0002349501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008631205,"threshold_uncertainty_score":0.9999442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009727109650713944,"score_gpt":0.2337839200246157,"score_spread":0.2240568103739018,"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."}}