{"id":"W4399731236","doi":"10.1101/2024.06.14.24308832","title":"Clinical exome sequencing data from patients with inborn errors of immunity: cohort level meta-analysis and the benefit of systematic reanalysis","year":2024,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Immunodeficiency and Autoimmune Disorders","field":"Immunology and Microbiology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nova Scotia Health Authority; Izaak Walton Killam Health Centre; Dalhousie University","funders":"","keywords":"Exome sequencing; Meta-analysis; Exome; Cohort; Medicine; Cohort study; Computational biology; Data science; Computer science; Genetics; Internal medicine; Biology; Mutation; Gene","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":[0.005450686,0.0005062717,0.00493726,0.0004752108,0.0001575859,0.00003671705,0.002102167,0.0005082787,0.0002779671],"category_scores_gemma":[0.0009229138,0.0002750088,0.001582069,0.0008468036,0.001384316,0.00006845434,0.003180356,0.001374079,0.00002444268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002920891,"about_ca_system_score_gemma":0.0001774498,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008322401,"about_ca_topic_score_gemma":0.000380025,"domain_scores_codex":[0.9941287,0.001865022,0.002500063,0.0009635595,0.0002486546,0.0002940016],"domain_scores_gemma":[0.991286,0.001992864,0.001878925,0.004484142,0.0003464457,0.0000115631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.0003742083,0.000313783,0.1188073,0.004694398,0.8721663,0.000003794087,0.002138166,0.0005655958,0.0005532854,0.0002091615,0.00001032074,0.0001635921],"study_design_scores_gemma":[0.001476015,0.00007378284,0.1842045,0.001022656,0.808649,0.000001908698,0.001527419,0.0007314548,0.0004586117,0.001361355,0.00001314104,0.000480132],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8963629,0.09925835,0.0003028553,0.00008383687,0.0003025348,0.0009178818,0.002640864,0.00002803397,0.0001027402],"genre_scores_gemma":[0.9959688,0.0005839517,0.0001273222,0.0000336444,0.000002309699,0.00008199659,0.002806538,0.00003360844,0.0003618446],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09960588,"threshold_uncertainty_score":0.9999702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1312980618354275,"score_gpt":0.3172791121129672,"score_spread":0.1859810502775397,"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."}}