{"id":"W2990490132","doi":"10.1074/mcp.r119.001743","title":"The Human Immunopeptidome Project: A Roadmap to Predict and Treat Immune Diseases","year":2019,"lang":"en","type":"article","venue":"Molecular & Cellular Proteomics","topic":"vaccines and immunoinformatics approaches","field":"Biochemistry, Genetics and Molecular Biology","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute; University of Ottawa; Centre Hospitalier Universitaire Sainte-Justine","funders":"Biotechnology and Biological Sciences Research Council; UK Research and Innovation; Epic Foundation; Wellcome Trust; Wellcome","keywords":"Context (archaeology); Precision medicine; Data science; Computer science; Computational biology; Medicine; Immunology; Biology","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":[0.0002634716,0.0003184777,0.0002588366,0.00006188254,0.0003048534,0.0002139789,0.0004704299,0.0001461314,0.00000735297],"category_scores_gemma":[0.00005116228,0.0002400652,0.0001680796,0.0001410797,0.00007208421,0.0000120677,0.0005157951,0.0001529299,0.00003565289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002425416,"about_ca_system_score_gemma":0.00008257613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004949267,"about_ca_topic_score_gemma":0.000002775955,"domain_scores_codex":[0.9984539,0.00007677524,0.0004088549,0.0004131164,0.0002000344,0.0004473476],"domain_scores_gemma":[0.9986783,0.000008565754,0.0001352745,0.0009914592,0.00007903662,0.0001073637],"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":[0.0001006298,0.00005213608,0.0009446837,0.00005837875,0.00009790131,0.000003612778,0.0001106913,0.00005694803,0.9969971,0.0003750638,0.0002186642,0.0009841803],"study_design_scores_gemma":[0.001155207,0.0007052096,0.001630007,0.00003556105,0.00005693212,0.00002400471,0.0002692976,0.0004088124,0.9766244,0.0001262119,0.01853274,0.0004316187],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910291,0.004301012,0.001126777,0.0001747298,0.00008853919,0.002134128,0.00002525277,0.00002635689,0.001094135],"genre_scores_gemma":[0.995383,0.0002075602,0.001106123,0.0001534646,0.00007727047,0.0002728369,0.0002451758,0.00006866793,0.002485852],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02037271,"threshold_uncertainty_score":0.9789575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00491413264152805,"score_gpt":0.2103838882524701,"score_spread":0.205469755610942,"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."}}