{"id":"W2950763275","doi":"10.1101/213264","title":"The C-terminal extension landscape of naturally presented HLA-I ligands","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":"","funders":"Ontario Ministry of Economic Development and Innovation; European Federation of Pharmaceutical Industries and Associations; Novartis Pharma; Wellcome Trust; Ministero dello Sviluppo Economico; Fundação de Amparo à Pesquisa do Estado de São Paulo; Diamond Light Source; Genome Canada; Pfizer","keywords":"Epitope; Human leukocyte antigen; Computational biology; Biology; Allele; Extension (predicate logic); HLA-A; Genetics; Chemistry; Antigen; Computer science; Gene","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003175312,0.0002222161,0.0002615183,0.0004585808,0.0001780946,0.0006532979,0.0001967424,0.0002717579,0.0006703058],"category_scores_gemma":[0.0006545138,0.0001327687,0.0002140226,0.0006173471,0.0001839948,0.000373265,0.000258209,0.0003454758,0.0002599442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002629188,"about_ca_system_score_gemma":0.0001784167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005778637,"about_ca_topic_score_gemma":0.0008433191,"domain_scores_codex":[0.9998631,0.00002462,0.000008550613,0.00004995652,0.00002737222,0.00002626097],"domain_scores_gemma":[0.9997358,0.00008106109,0.00007729956,0.0000296316,0.00003990289,0.00003622916],"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":[0.001158913,0.000193506,0.1701735,0.000372751,0.0002395762,0.0007372714,0.0002692375,0.05429538,0.7422802,0.00162359,0.002070142,0.02658593],"study_design_scores_gemma":[0.00005469364,0.0004729911,0.3071965,0.00004839104,0.0001550439,0.00122366,0.0007094487,0.4939006,0.1838983,0.006001064,0.006266765,0.00007240293],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966385,0.0001962321,0.001858077,0.00003862774,0.000002243589,0.000002802831,0.0009239427,0.0000524842,0.0002870429],"genre_scores_gemma":[0.9924522,0.0001535222,0.003679189,0.00002745117,0.000003553101,0.000006527851,0.003497466,0.00002265859,0.0001574808],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006703058,"threshold_uncertainty_score":0.002242446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0118211661443075,"score_gpt":0.2278646381077703,"score_spread":0.2160434719634628,"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."}}