{"id":"W2268300422","doi":"10.1038/ni.3373","title":"Central tolerance: what you see is what you don't get!","year":2016,"lang":"en","type":"letter","venue":"Nature Immunology","topic":"T-cell and B-cell Immunology","field":"Immunology and Microbiology","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Princess Margaret Cancer Centre","funders":"","keywords":"Repertoire; Biology; Central tolerance; Self Tolerance; Immunology; Cell biology; Antigen; Selection (genetic algorithm); Negative selection; T cell; Immune tolerance; Genetics; Gene; Computer science; Immune system; Genome","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","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.0004116929,0.002111102,0.00272885,0.0008918999,0.0007504075,0.0004385969,0.003257372,0.02620214,0.01457709],"category_scores_gemma":[0.0001294376,0.001679973,0.001165561,0.0004656058,0.002505946,0.001714849,0.001020749,0.01968711,0.01032072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005235319,"about_ca_system_score_gemma":0.0005214753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00012087,"about_ca_topic_score_gemma":0.00002765337,"domain_scores_codex":[0.9897622,0.001330268,0.00156438,0.002745002,0.0002475274,0.004350637],"domain_scores_gemma":[0.9944907,0.0006971505,0.001123721,0.003097191,0.0005175812,0.00007364332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004459747,0.00011824,0.00005429923,0.00008786716,0.001974886,0.0004703266,0.0005358939,2.2222e-7,0.3176156,0.0001211044,0.6453182,0.03325743],"study_design_scores_gemma":[0.004120118,0.0005205238,0.00009340325,0.0007632662,0.0003532279,0.001805084,0.000552714,3.107361e-7,0.09881585,0.0007359931,0.8905157,0.001723775],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.01021374,0.4078401,0.00002528616,0.5158371,0.06259373,0.0009883846,0.0003676952,0.0005647962,0.001569163],"genre_scores_gemma":[0.01610634,0.1088478,0.00006843441,0.6838587,0.00681819,0.0002516747,0.004813434,0.0004491406,0.1787863],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.2989923,"threshold_uncertainty_score":0.999163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006106948899582122,"score_gpt":0.2181256287518257,"score_spread":0.2120186798522436,"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."}}