{"id":"W2769205261","doi":"10.1101/219576","title":"Quantifying Immune-Based Counterselection of Somatic Mutations","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"vaccines and immunoinformatics approaches","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; Lunenfeld-Tanenbaum Research Institute; Institute of Cancer Research; Ontario Institute for Cancer Research; University of Toronto","funders":"","keywords":"Somatic cell; Major histocompatibility complex; Biology; Allele; Immune system; Germline mutation; Genetics; Germline; MHC class I; Mutation; Computational biology; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007331703,0.0002540144,0.0002568489,0.0006544602,0.0001336641,0.0003804135,0.0002709905,0.000340276,0.001344025],"category_scores_gemma":[0.000960876,0.0001257436,0.0001194897,0.0002846267,0.0003963222,0.0002293842,0.0002703977,0.0005854261,0.0002350493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002894634,"about_ca_system_score_gemma":0.00009650925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002283133,"about_ca_topic_score_gemma":0.0002892692,"domain_scores_codex":[0.9993019,0.0001659012,0.0000292792,0.0001742509,0.0002581719,0.00007053323],"domain_scores_gemma":[0.9992765,0.0003318862,0.0001549479,0.00005557017,0.0001215361,0.0000595545],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001544157,0.00004827879,0.007498253,0.00005352829,0.00002731242,0.00002595497,0.00004579409,0.0009790288,0.9829957,0.0003723297,0.0001021972,0.007697177],"study_design_scores_gemma":[0.000008597754,0.0002232155,0.02166597,0.000006716819,0.00002853656,0.0001696789,0.00003768242,0.0153104,0.9611759,0.0003867215,0.0009757187,0.00001085887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9675835,0.001119231,0.02851963,0.00009771447,0.00003598107,0.00003947905,0.0003402143,0.0002033616,0.002060925],"genre_scores_gemma":[0.9885826,0.0002796271,0.009711819,0.00009629083,0.00001270831,0.00003930663,0.0001840553,0.00004367056,0.001049897],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001344025,"threshold_uncertainty_score":0.004496217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02420544676347659,"score_gpt":0.2465739562070022,"score_spread":0.2223685094435257,"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."}}