{"id":"W3203928808","doi":"10.3390/cancers13205034","title":"Reinspection of a Clinical Proteomics Tumor Analysis Consortium (CPTAC) Dataset with Cloud Computing Reveals Abundant Post-Translational Modifications and Protein Sequence Variants","year":2021,"lang":"en","type":"article","venue":"Cancers","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto; McGill University Health Centre","funders":"Los Alamos National Laboratory; National Cancer Institute; National Nuclear Security Administration; National Institute of Standards and Technology; U.S. Department of Energy","keywords":"Proteogenomics; Biology; Proteomics; Computational biology; Genetics; Sequence analysis; Sequence (biology); Sequence database; Protein sequencing; Bioinformatics; Peptide sequence; Genomics; Gene; Genome","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":[0.0002271503,0.0001354284,0.0003312666,0.00006184886,0.0001648308,0.00002797478,0.0001374331,0.00007694102,0.00005607209],"category_scores_gemma":[0.000128022,0.0001355131,0.00007303343,0.0005636608,0.0002443568,0.00009884933,0.00004035617,0.0002470056,7.990344e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001781883,"about_ca_system_score_gemma":0.001023437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00031266,"about_ca_topic_score_gemma":0.0001118121,"domain_scores_codex":[0.9985543,0.00003691568,0.0005973674,0.0004827434,0.0001639044,0.000164756],"domain_scores_gemma":[0.9985506,0.00007705899,0.0004653828,0.000498817,0.000311826,0.00009634942],"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":[0.0002990355,0.0001306615,0.01268997,0.0003439107,0.0007221503,0.00002639329,0.0002060791,0.01784538,0.9386424,0.02758065,0.0001407141,0.001372623],"study_design_scores_gemma":[0.003394522,0.0002497513,0.01646949,0.0009026122,0.001695356,0.0002312453,0.001060191,0.155917,0.7998578,0.01315031,0.005438551,0.001633152],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7638063,0.00007476431,0.2303343,0.0003959359,0.00001385247,0.0004679966,0.004398821,0.00006854899,0.0004394633],"genre_scores_gemma":[0.8340932,0.00004502103,0.1641342,0.00006912023,0.00008623307,0.0001432204,0.00133962,0.00001495363,0.00007440505],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1387846,"threshold_uncertainty_score":0.5526063,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04170524928759867,"score_gpt":0.3482304642294535,"score_spread":0.3065252149418548,"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."}}