{"id":"W4413114150","doi":"10.3390/cells14151223","title":"Exploiting TCR Repertoire Analysis to Select Therapeutic TCRs for Cancer Immunotherapy","year":2025,"lang":"en","type":"review","venue":"Cells","topic":"CAR-T cell therapy research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Infection and Immunity","funders":"Medical Research Council; Chulabhorn Royal Academy","keywords":"T-cell receptor; Immunotherapy; Cancer immunotherapy; Antigen; Cancer; Adoptive cell transfer; T cell; Biology; Computational biology; Immunology; Immune system; Cancer research; Medicine; 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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007066038,0.0006477284,0.003412222,0.001309815,0.0001454608,0.00009080236,0.000509003,0.0004239681,0.002772477],"category_scores_gemma":[0.00007547985,0.0005132456,0.002446609,0.003414991,0.00005590741,0.00003623204,0.00008032336,0.0006057682,0.00004996524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008210233,"about_ca_system_score_gemma":0.001417079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001693484,"about_ca_topic_score_gemma":0.00005908255,"domain_scores_codex":[0.9965469,0.0002315954,0.0008699009,0.001009842,0.0005170253,0.0008247533],"domain_scores_gemma":[0.9969501,0.0009710147,0.0002504991,0.001269336,0.0003250833,0.0002339292],"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":[0.0001226292,0.00007253288,0.000005113464,0.01171025,0.007859653,0.00001751423,0.0001818835,0.000007191081,0.001644933,0.000006564218,0.001965926,0.9764058],"study_design_scores_gemma":[0.0005595047,0.0001967279,0.000001611482,0.007089609,0.00720135,0.000008402903,0.00003786199,0.00002932613,0.001434683,0.000009976981,0.9829931,0.0004378205],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00001956356,0.9919,0.001086218,0.000234426,0.0003564249,0.004495046,0.0001059139,0.0001786234,0.001623816],"genre_scores_gemma":[0.000006989727,0.9019037,0.0003923077,0.0008717878,0.0005006753,0.002363734,0.0001588404,0.0002259637,0.09357599],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9810272,"threshold_uncertainty_score":0.9997319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08142222239966064,"score_gpt":0.4294910818292818,"score_spread":0.3480688594296212,"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."}}