{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009055242,0.0007121572,0.0005016281,0.0008582486,0.0002734342,0.0006650695,0.001122186,0.0006025293,0.004550741],"category_scores_gemma":[0.001356099,0.0003651931,0.0004620289,0.0004894321,0.000254995,0.0004685397,0.0004782214,0.0007196472,0.001727646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004118677,"about_ca_system_score_gemma":0.0003841053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001511583,"about_ca_topic_score_gemma":0.001758466,"domain_scores_codex":[0.9997403,0.00004417162,0.00001290171,0.00008649785,0.00008332613,0.00003283883],"domain_scores_gemma":[0.9996306,0.0001355539,0.00007939888,0.00005626037,0.00007221371,0.00002603458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001128985,0.0005881618,0.0194252,0.0007375057,0.000470538,0.0005824416,0.0002309275,0.1714789,0.2862369,0.006945547,0.05668892,0.4554859],"study_design_scores_gemma":[0.00001888891,0.00004798341,0.004002284,0.000007954175,0.00001320458,0.0001050235,0.00001446565,0.9492258,0.04207106,0.001268195,0.003192832,0.00003227207],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1920009,0.0002664588,0.7499257,0.0001972381,0.00006099364,0.0001909555,0.005272359,0.04923047,0.002854954],"genre_scores_gemma":[0.4754411,0.000151365,0.5120323,0.0002063125,0.0000406974,0.0004743481,0.005755956,0.00217807,0.00371981],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004550741,"threshold_uncertainty_score":0.0152238,"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."}}