{"id":"W4251781653","doi":"10.1158/1538-7445.am2019-3383","title":"Abstract 3383: EPIC: MHC-I epitope prediction integrating mass spectrometry derived motifs and tissue-specific expression profiles","year":2019,"lang":"en","type":"article","venue":"Cancer Research","topic":"vaccines and immunoinformatics approaches","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Epitope; Human leukocyte antigen; Computational biology; Major histocompatibility complex; Biology; Gene; Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009252817,0.001109773,0.0005273655,0.0007415426,0.0002352814,0.0004813594,0.000704817,0.0005565656,0.008868018],"category_scores_gemma":[0.001544699,0.0002735451,0.0006519199,0.0007167038,0.0001521099,0.0003932238,0.0004706696,0.0004926705,0.005150045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000294544,"about_ca_system_score_gemma":0.0004241024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001598545,"about_ca_topic_score_gemma":0.002013578,"domain_scores_codex":[0.9997028,0.00004581644,0.00001758091,0.000123497,0.00008185545,0.00002839355],"domain_scores_gemma":[0.9995747,0.0001739013,0.00005978075,0.00006157126,0.00009548746,0.0000345624],"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":[0.004176992,0.0007742617,0.09736332,0.001632441,0.0006062272,0.001094277,0.0001833813,0.06577911,0.391597,0.002572662,0.1488865,0.2853338],"study_design_scores_gemma":[0.000589412,0.0009420932,0.1320409,0.00007705118,0.0002161275,0.000951535,0.0000613411,0.6735449,0.1332254,0.004993797,0.05317604,0.0001813436],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4578221,0.001197087,0.293054,0.000652043,0.0003194821,0.0004339454,0.1640665,0.0738027,0.008652195],"genre_scores_gemma":[0.5239676,0.0006061039,0.2627442,0.0003899576,0.0001897119,0.0007873165,0.1986689,0.002125468,0.01052078],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008868018,"threshold_uncertainty_score":0.02966642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0367652546446296,"score_gpt":0.3239035279656309,"score_spread":0.2871382733210013,"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."}}