{"id":"W4296239734","doi":"10.1002/prot.26428","title":"<scp>MHC2AffyPred</scp> : A machine‐learning approach to estimate affinity of <scp>MHC</scp> class <scp>II</scp> peptides based on structural interaction fingerprints","year":2022,"lang":"en","type":"article","venue":"Proteins Structure Function and Bioinformatics","topic":"vaccines and immunoinformatics approaches","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"FPInnovations","funders":"Gujarat Council on Science and Technology","keywords":"Major histocompatibility complex; Peptide; MHC class I; Perl; Computational biology; Docking (animal); Chemistry; Computer science; Biology; Biochemistry; Programming language","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":[0.0004851718,0.0006126768,0.000523355,0.0003819158,0.0009823014,0.000196047,0.0004361936,0.0003022638,0.00001269823],"category_scores_gemma":[0.0011235,0.0005315667,0.0002285013,0.0004972289,0.00008879173,0.00009035994,0.0007324838,0.0008816629,0.000005920254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000915965,"about_ca_system_score_gemma":0.0001396342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003092818,"about_ca_topic_score_gemma":0.00001370181,"domain_scores_codex":[0.9971955,0.0001429201,0.0009564194,0.0004692241,0.0006127189,0.0006231888],"domain_scores_gemma":[0.9979619,0.0001315977,0.0008507979,0.0005989279,0.0002149517,0.0002418459],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007358446,0.001172166,0.02342214,0.005411289,0.001515346,0.000005126325,0.02215498,0.6227788,0.2543952,0.002069584,0.01606919,0.05027023],"study_design_scores_gemma":[0.003062527,0.004959373,0.01298864,0.0001148394,0.0002048718,0.0001727584,0.01093533,0.8191619,0.07812389,0.0003740845,0.06960785,0.0002939576],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.979412,0.0001472284,0.0123877,0.00004173387,0.0004931398,0.001348713,0.0002780358,0.0001028705,0.005788642],"genre_scores_gemma":[0.9783057,0.00002532576,0.01880466,0.0004138097,0.0001434602,0.0001412906,0.00138736,0.00006005107,0.0007183671],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.196383,"threshold_uncertainty_score":0.9997136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01037782350277831,"score_gpt":0.2267041958729424,"score_spread":0.2163263723701641,"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."}}