{"id":"W4400497719","doi":"10.1093/bioinformatics/btae405","title":"Geometric epitope and paratope prediction","year":2024,"lang":"en","type":"article","venue":"Bioinformatics","topic":"vaccines and immunoinformatics approaches","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"H2020 European Research Council; Sapienza Università di Roma; European Commission","keywords":"Paratope; Epitope; Computer science; Computational biology; Artificial intelligence; Biology; Antibody; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001715564,0.0001184689,0.00009028098,0.0001160252,0.00006520761,0.000152392,0.000088754,0.000101733,0.00001134243],"category_scores_gemma":[0.00003931455,0.00009542882,0.0000452874,0.0002111835,0.00002788838,0.00002447321,0.0001005408,0.00007258342,0.00005718392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007971045,"about_ca_system_score_gemma":0.00003836367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002137164,"about_ca_topic_score_gemma":5.668034e-7,"domain_scores_codex":[0.9993622,0.000006081177,0.0002783956,0.0000967682,0.0000946466,0.0001619237],"domain_scores_gemma":[0.9996727,0.000008817755,0.00003686343,0.0001956467,0.00002925551,0.00005673143],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009044734,0.0001160379,0.005556467,0.002517097,0.0005961706,0.00000673623,0.002203805,0.0002910068,0.02399235,0.005778806,0.1614422,0.7974089],"study_design_scores_gemma":[0.0006087035,0.0006209132,0.005315289,0.00009547776,0.00007236309,0.0002510806,0.0008224389,0.1315778,0.01926832,0.0001752886,0.8407049,0.000487453],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.913222,0.02058016,0.04319618,0.0003239269,0.001092951,0.0005712059,0.0001411115,0.0001705115,0.02070193],"genre_scores_gemma":[0.9870371,0.003777404,0.007512851,0.0002005052,0.0002458275,0.00001999113,0.0002709366,0.00002137572,0.0009140651],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7969214,"threshold_uncertainty_score":0.3891474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01213177767484656,"score_gpt":0.2260804010779345,"score_spread":0.2139486234030879,"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."}}