{"id":"W4226385249","doi":"10.2139/ssrn.4048386","title":"Population Based Selection Shapes the T Cell Receptor Repertoire During Thymic Development","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"T-cell and B-cell Immunology","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Infection and Immunity","funders":"","keywords":"Repertoire; Selection (genetic algorithm); Population; Biology; Receptor; Evolutionary biology; T-cell receptor; Computational biology; Immunology; Genetics; T cell; Computer science; Artificial intelligence; Sociology; Demography; Immune system","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":[0.0002901634,0.0001734492,0.0003286614,0.000386807,0.0002045631,0.001150594,0.0003784706,0.0002733722,0.00266737],"category_scores_gemma":[0.0006921504,0.0003134562,0.0001903113,0.0002181202,0.0002694966,0.0003622839,0.000531727,0.0008387371,0.001148473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003298378,"about_ca_system_score_gemma":0.0001780294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002520581,"about_ca_topic_score_gemma":0.0009311421,"domain_scores_codex":[0.9997103,0.00006242532,0.00001075205,0.00006303481,0.00008156952,0.0000719782],"domain_scores_gemma":[0.9994946,0.0002150448,0.00007664522,0.00003036468,0.00009380376,0.00008963537],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001308516,0.00002469549,0.006057939,0.00002777153,0.00001300153,0.0001307031,0.0001115125,0.0008126408,0.9785411,0.0008297276,0.0001476031,0.01317251],"study_design_scores_gemma":[0.00008475853,0.001164621,0.3522947,0.00008164383,0.0001875162,0.002011162,0.001135061,0.03637114,0.5924447,0.003785268,0.01034776,0.00009172899],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918191,0.0005447155,0.003496201,0.00004094493,0.00001595901,0.000006177234,0.00004361185,0.00005781434,0.003975339],"genre_scores_gemma":[0.9956936,0.0003558174,0.001260084,0.00005673945,0.00001930803,0.00001294372,0.00009421687,0.00008988446,0.002417373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00266737,"threshold_uncertainty_score":0.008923233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005320560249847384,"score_gpt":0.1905858396380583,"score_spread":0.1852652793882109,"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."}}