{"id":"W3164118400","doi":"10.1136/annrheumdis-2021-eular.1107","title":"OP0018 PREDICTING RESPONSES TO ANTI-TNF TREATMENTS IN RHEUMATOID ARTHRITIS PATIENTS FROM GENETIC AND CLINICAL DATA USING A MACHINE LEARNING APPROACH","year":2021,"lang":"en","type":"article","venue":"Annals of the Rheumatic Diseases","topic":"Rheumatoid Arthritis Research and Therapies","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Montreal Clinical Research Institute; Jewish General Hospital; McGill University","funders":"","keywords":"Medicine; Linkage disequilibrium; Single-nucleotide polymorphism; Rheumatoid arthritis; Genome-wide association study; SNP; Genetic association; Internal medicine; Oncology; Bioinformatics; Genotype; Genetics; Gene; Biology","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":[0.0008442409,0.0004723415,0.0006424366,0.001549047,0.0001905474,0.0006643121,0.0003637071,0.0005892158,0.001850873],"category_scores_gemma":[0.003461735,0.0001127584,0.0007789203,0.000917908,0.0001633542,0.000296742,0.0003025375,0.0005709771,0.0004526033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002603284,"about_ca_system_score_gemma":0.0003359434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002302534,"about_ca_topic_score_gemma":0.002401994,"domain_scores_codex":[0.9994603,0.0001964563,0.00006438296,0.0001324893,0.00008671585,0.00005970799],"domain_scores_gemma":[0.9977371,0.001516397,0.0003816456,0.00008498489,0.0001608658,0.0001189134],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003350616,0.0006176011,0.8894759,0.00008887694,0.0009444121,0.0006133368,0.00003873356,0.01722229,0.005214598,0.0002349525,0.00144492,0.08075382],"study_design_scores_gemma":[0.0005031091,0.001688514,0.5766495,0.00006517919,0.000954402,0.001691103,0.0001915716,0.4083238,0.004134831,0.002968583,0.002766786,0.00006259393],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918149,0.0004657117,0.004182384,0.000321211,0.0000291667,0.00002416038,0.002231126,0.00007811467,0.0008532241],"genre_scores_gemma":[0.9937369,0.0001000889,0.003127171,0.00006577431,0.00004498931,0.00001980639,0.002486935,0.00000560645,0.0004127707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002302534,"threshold_uncertainty_score":0.00619179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09515230628081905,"score_gpt":0.36972063766215,"score_spread":0.2745683313813309,"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."}}