{"id":"W2920595125","doi":"10.1101/567081","title":"EPIP: MHC-I epitope prediction integrating mass spectrometry derived motifs and tissue-specific expression profiles","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"vaccines and immunoinformatics approaches","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Science, Technology and Innovation Commission of Shenzhen Municipality; Government of Jiangxi Province; National Natural Science Foundation of China","keywords":"Epitope; Human leukocyte antigen; Computational biology; Biology; Antigen; Genetics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004389002,0.0006108966,0.000524608,0.0001942202,0.0001809048,0.0002937478,0.000465026,0.0007648716,0.00002555905],"category_scores_gemma":[0.0001322213,0.0005822357,0.000126437,0.0001885838,0.000081306,0.00003145295,0.0007650983,0.000631755,0.000023939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008477695,"about_ca_system_score_gemma":0.0001858334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001073621,"about_ca_topic_score_gemma":3.844898e-7,"domain_scores_codex":[0.9975399,0.0001038505,0.0006518572,0.0009416981,0.0002665584,0.0004960817],"domain_scores_gemma":[0.9978037,0.00002052535,0.0004991173,0.001244443,0.0002648322,0.000167422],"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":[0.00004426825,0.00005055138,0.004112485,0.0003959752,0.00009177208,0.000002944358,0.00001771235,0.00006991576,0.9946944,0.00006380497,0.0004407338,0.00001545197],"study_design_scores_gemma":[0.0004993604,0.000176211,0.02596107,0.0003693971,0.00004494409,1.050447e-7,0.00003708656,0.0007832345,0.9675305,0.00000244237,0.003997018,0.0005986171],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9746237,0.005577242,0.0174823,0.00006169851,0.0009467301,0.0009529302,0.000206935,0.0001094208,0.00003902937],"genre_scores_gemma":[0.9709471,0.002811451,0.02522979,0.00004387361,0.0006748322,0.0001364135,0.00001356022,0.0001204702,0.00002250048],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02716387,"threshold_uncertainty_score":0.9996629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01069693196369238,"score_gpt":0.2058768632672742,"score_spread":0.1951799313035818,"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."}}