{"id":"W2790340314","doi":"10.1371/journal.pone.0191087","title":"Environmental epidemiology of Kawasaki disease: Linking disease etiology, pathogenesis and global distribution","year":2018,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Kawasaki Disease and Coronary Complications","field":"Medicine","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"","keywords":"Epidemiology; Kawasaki disease; Incidence (geometry); Context (archaeology); Disease; Population; Pathogenesis; Etiology; Environmental health; Immunology; Medicine; Environmental epidemiology; Demography; Biology; Pathology; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001108877,0.0001251009,0.0002963215,0.00002307855,0.000115036,0.000001940657,0.00007440081,0.00005923757,0.0001576267],"category_scores_gemma":[0.0002023854,0.0001197708,0.00007662529,0.00007685917,0.0004973998,0.00004575872,0.00009380245,0.00005807821,0.00003892811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007411959,"about_ca_system_score_gemma":0.00006077257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005976125,"about_ca_topic_score_gemma":0.00000136339,"domain_scores_codex":[0.998943,0.0001037671,0.0002794606,0.0003209021,0.0001350454,0.000217877],"domain_scores_gemma":[0.9989492,0.0000819936,0.0001054969,0.0003739849,0.00004193608,0.00044738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004597966,0.001540581,0.9900587,0.0001476351,0.0001391589,0.00001019295,0.000009128334,4.233848e-7,0.003057186,0.002444865,0.0000479996,0.002084287],"study_design_scores_gemma":[0.0004346684,0.0001904856,0.9950909,0.0001824345,0.0008267067,0.000004472058,0.00001586969,0.0004588077,0.0001592471,0.00242632,0.0001072226,0.0001028539],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923335,0.003012074,0.0009488292,0.001636621,0.00001999157,0.0003095952,0.001612988,0.00004596783,0.00008047413],"genre_scores_gemma":[0.9968719,0.0004878826,0.0004391249,0.0004304998,0.0002140557,0.00004588582,0.001465642,0.00001022932,0.00003472118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005032165,"threshold_uncertainty_score":0.4884112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05277946511592881,"score_gpt":0.2837395014291633,"score_spread":0.2309600363132345,"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."}}