{"id":"W2741742659","doi":"10.1093/nar/gkx664","title":"The SysteMHC Atlas project","year":2017,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"vaccines and immunoinformatics approaches","field":"Biochemistry, Genetics and Molecular Biology","cited_by":144,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Institute for Research in Immunology and Cancer","funders":"National Institute of Allergy and Infectious Diseases; National Institute of General Medical Sciences; Norges Forskningsråd; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Cancer Institute; National Institutes of Health; National Science Foundation","keywords":"Biology; Major histocompatibility complex; Computational biology; Pipeline (software); Context (archaeology); Atlas (anatomy); Computer science; Data science; Genetics; Antigen","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.001495211,0.0001004149,0.0000977098,0.00003540638,0.002090453,0.000588378,0.001091767,0.0001156687,0.000007155985],"category_scores_gemma":[0.0005875998,0.00006206775,0.00007499741,0.00005193678,0.0002504506,0.000009930814,0.0007598739,0.0002349655,0.0001186365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001788761,"about_ca_system_score_gemma":0.0001318243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008035835,"about_ca_topic_score_gemma":0.00002973682,"domain_scores_codex":[0.9987411,0.00009438042,0.0001869034,0.0001944277,0.00033591,0.0004473047],"domain_scores_gemma":[0.9982162,0.00002726695,0.0000803295,0.00141187,0.0002131633,0.00005124617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008297868,0.0002170008,0.01551383,0.0004262139,0.0004510497,0.00002063575,0.001009524,0.00000963911,0.4422958,0.01329877,0.3994489,0.1264788],"study_design_scores_gemma":[0.0006103779,0.0004014529,0.008518465,0.00003375503,0.000005778679,0.00003916826,0.001322488,0.0008220574,0.02823266,0.0001868874,0.9596329,0.0001940348],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9275333,0.00116839,0.00004808144,0.001096229,0.0001896083,0.0005599764,0.000007422665,0.00001240413,0.06938463],"genre_scores_gemma":[0.9888626,0.0006255381,0.0001625137,0.00001917647,0.0002906677,0.00006701114,0.0000139154,0.00002103193,0.009937554],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.560184,"threshold_uncertainty_score":0.9992087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06768324745799226,"score_gpt":0.3618527550203449,"score_spread":0.2941695075623527,"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."}}