{"id":"W4409645431","doi":"10.1093/gpbjnl/qzaf033","title":"TRAIT: A Comprehensive Database for T-cell Receptor–antigen Interactions","year":2025,"lang":"en","type":"article","venue":"Genomics Proteomics & Bioinformatics","topic":"CAR-T cell therapy research","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Zhejiang University; Natural Science Foundation of Zhejiang Province; National Natural Science Foundation of China","keywords":"T-cell receptor; Antigen; Biology; Trait; Computational biology; T cell; Binding affinities; Chimeric antigen receptor; Database; Immunology; Receptor; Computer science; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003647166,0.000305865,0.0005003844,0.0006054639,0.0002632148,0.0001206812,0.0003455861,0.0001598945,0.0003708877],"category_scores_gemma":[0.0001096369,0.000305129,0.0002761631,0.0004934125,0.0001410934,0.000226968,0.0002255561,0.0005266856,0.0001538635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005071901,"about_ca_system_score_gemma":0.0008348392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002751012,"about_ca_topic_score_gemma":0.00001357563,"domain_scores_codex":[0.9980552,0.00002914294,0.0008193327,0.0002838852,0.0002378393,0.0005745789],"domain_scores_gemma":[0.9980925,0.000211264,0.0002180305,0.0008183486,0.0004489608,0.0002109371],"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":[0.00154749,0.0003476679,0.0001400444,0.001399406,0.0003280835,0.000003110107,0.002108737,0.00006245327,0.9424251,0.001406269,0.02115724,0.02907437],"study_design_scores_gemma":[0.0049655,0.000368581,0.00008308799,0.0001975672,0.0001330603,0.00003863232,0.002064225,0.04688156,0.239902,0.0004819913,0.7045009,0.0003829992],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6656302,0.000406291,0.2749808,0.003586945,0.001529107,0.01412567,0.002010143,0.0002902217,0.03744063],"genre_scores_gemma":[0.01891097,0.001597248,0.9409082,0.004246654,0.000513168,0.0009764459,0.002675397,0.0001475472,0.03002439],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7025232,"threshold_uncertainty_score":0.9999401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03631192317494432,"score_gpt":0.326807436567054,"score_spread":0.2904955133921097,"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."}}