{"id":"W4313527435","doi":"10.1109/bibm55620.2022.9995066","title":"Unseen Epitope-TCR Interaction Prediction based on Amino Acid Physicochemical Properties","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","topic":"vaccines and immunoinformatics approaches","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Science and Engineering Research Council","keywords":"Epitope; T-cell receptor; Computational biology; Amino acid; Computer science; Artificial intelligence; Sequence (biology); Product (mathematics); Epitope mapping; T cell; Antigen; Chemistry; Biology; Mathematics; Biochemistry; Immune system; 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":[0.0002651532,0.0002448687,0.0001980414,0.0002572749,0.0002238404,0.00008928341,0.0003327684,0.00008228776,0.0002067571],"category_scores_gemma":[0.00004197098,0.0001967426,0.00008490762,0.000157183,0.00009195066,0.00003404778,0.0001688749,0.0003062104,0.00001592959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000730889,"about_ca_system_score_gemma":0.00007997502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001504774,"about_ca_topic_score_gemma":0.000001581864,"domain_scores_codex":[0.998471,0.00003439121,0.0004926366,0.0002424952,0.0005423999,0.000217053],"domain_scores_gemma":[0.9992449,0.00001378127,0.0002468025,0.0002797528,0.0001278727,0.000086848],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001748934,0.0007191529,0.0006354616,0.0001921171,0.0003032956,0.00000460707,0.0009788568,0.001210593,0.9218174,0.00146218,0.02889151,0.04203594],"study_design_scores_gemma":[0.00286995,0.004077998,0.000651155,0.000174808,0.0000505494,0.00007397957,0.004043792,0.7736658,0.1577898,0.0001251328,0.05592785,0.0005491583],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9712955,0.0001344258,0.002794098,0.004590257,0.002405474,0.0007005084,0.0005521028,0.00006520422,0.01746239],"genre_scores_gemma":[0.9955059,0.0002495358,0.0002970798,0.001587861,0.0003226341,0.0001063529,0.001453418,0.00001698678,0.0004602299],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7724552,"threshold_uncertainty_score":0.8022929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0403913250873883,"score_gpt":0.2643326205174773,"score_spread":0.223941295430089,"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."}}