{"id":"W1990367476","doi":"10.1186/1753-6561-1-s1-s120","title":"Application of bivariate mixed counting process models to genetic analysis of rheumatoid arthritis severity","year":2007,"lang":"en","type":"article","venue":"BMC Proceedings","topic":"Rheumatoid Arthritis Research and Therapies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto; Toronto Public Health; Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital","funders":"Canadian Institutes of Health Research; Mitacs","keywords":"Rheumatoid arthritis; Bivariate analysis; Candidate gene; Medicine; Single-nucleotide polymorphism; Univariate; PTPN22; Disease; Gene; Internal medicine; Genetics; Biology; Multivariate statistics; Genotype; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.02098793,0.001946966,0.002707125,0.002966852,0.0009122294,0.00232431,0.003080908,0.001893232,0.003226648],"category_scores_gemma":[0.05258262,0.0009758817,0.004116019,0.003165523,0.001523654,0.001677131,0.002353483,0.002659682,0.0005309476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002074304,"about_ca_system_score_gemma":0.002056369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01837201,"about_ca_topic_score_gemma":0.01330488,"domain_scores_codex":[0.9887275,0.008858719,0.0002961372,0.001072969,0.0005716677,0.0004729932],"domain_scores_gemma":[0.9536931,0.03999316,0.002438804,0.001760622,0.00148777,0.0006265519],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003709744,0.0001599894,0.0222676,0.0001098504,0.0009759699,0.00051809,0.0003606167,0.8005179,0.0007155741,0.13334,0.0008917336,0.03977185],"study_design_scores_gemma":[0.00004063202,0.00005580375,0.001163187,0.00001193296,0.00006947253,0.00005458123,0.00002669154,0.9578776,0.0000895714,0.0401665,0.0004164593,0.00002756483],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04643795,0.0003606011,0.9510532,0.0004698215,0.00008191133,0.0001351504,0.0003490056,0.0002812768,0.0008310859],"genre_scores_gemma":[0.6922328,0.0009138527,0.2994384,0.0002556728,0.0002487565,0.001121462,0.001128372,0.0001327696,0.004527852],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02098793,"threshold_uncertainty_score":0.1109961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01895167173294861,"score_gpt":0.2842608842784631,"score_spread":0.2653092125455145,"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."}}