{"id":"W6939384653","doi":"10.6084/m9.figshare.14205308","title":"Additional file 1 of A meta-analysis of the epidemiology of giant cell arteritis across time and space","year":2021,"lang":"en","type":"article","venue":"Figshare","topic":"Vasculitis and related conditions","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Giant cell arteritis; Incidence (geometry); Epidemiology; Table (database); Temporal artery; Giant cell","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004181557,0.002051193,0.003190202,0.003527445,0.0008500399,0.001953071,0.002409139,0.001669132,0.825376],"category_scores_gemma":[0.06608507,0.001147868,0.005261297,0.00543967,0.0003884009,0.002454731,0.001339751,0.001378378,0.04735015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001453719,"about_ca_system_score_gemma":0.002890723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007805549,"about_ca_topic_score_gemma":0.01590541,"domain_scores_codex":[0.9979745,0.0006257113,0.0003698419,0.0005063919,0.0003066724,0.000216853],"domain_scores_gemma":[0.9312466,0.06123983,0.002877522,0.002040963,0.002155648,0.0004394109],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.002411098,0.0002031075,0.007536193,0.1319394,0.004918275,0.0002621124,0.0002332911,0.002805503,0.0003547257,0.003474929,0.8279267,0.0179346],"study_design_scores_gemma":[0.07818117,0.002488059,0.09406071,0.06055235,0.03136516,0.003036093,0.0008068192,0.01332332,0.001655718,0.04589407,0.66794,0.000696491],"study_design_candidate":"meta_analysis","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.0004786604,0.0003326415,0.0007406172,0.0001623063,0.00006114554,0.0003488534,0.9970297,0.0001974246,0.0006487587],"genre_scores_gemma":[0.06083192,0.002442267,0.03101449,0.003081123,0.00074904,0.0350999,0.8368416,0.002140202,0.02779939],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.825376,"threshold_uncertainty_score":0.24908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05869197094585962,"score_gpt":0.2917135308437557,"score_spread":0.2330215598978961,"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."}}