{"id":"W2160996683","doi":"10.1093/jamia/ocu002","title":"Using age, triage score, and disposition data from emergency department electronic records to improve Influenza-like illness surveillance","year":2015,"lang":"en","type":"article","venue":"Journal of the American Medical Informatics Association","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; McGill University","funders":"","keywords":"Triage; Medicine; Emergency department; Confidence interval; Emergency medicine; Influenza-like illness; Early warning score; Pediatrics; Medical emergency; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006006547,0.0009598936,0.0007347899,0.001715102,0.0002417416,0.0008680757,0.0006747305,0.0005867841,0.0009215868],"category_scores_gemma":[0.02108003,0.0003371271,0.0009907212,0.001327591,0.0001895679,0.0009685571,0.0007304459,0.00072973,0.0002449672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000792245,"about_ca_system_score_gemma":0.001451038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02996418,"about_ca_topic_score_gemma":0.0415957,"domain_scores_codex":[0.9976138,0.001398182,0.000164832,0.0004538471,0.000245671,0.0001236804],"domain_scores_gemma":[0.9905524,0.004330259,0.003296951,0.0005709342,0.0008977739,0.0003516069],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001383762,0.00009868436,0.9837111,0.0000378999,0.0003118092,0.00002613314,0.00004259949,0.004333642,0.0001189377,0.00004926617,0.0004092097,0.01072234],"study_design_scores_gemma":[0.00006620854,0.0006644781,0.871049,0.0001021748,0.0003574585,0.0001148049,0.00009357351,0.1259831,0.0003809247,0.0002942054,0.0008631003,0.00003083926],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9831024,0.001370551,0.01061164,0.0006120008,0.00006897371,0.0001093809,0.00277655,0.0001680245,0.001180412],"genre_scores_gemma":[0.9924016,0.0002706631,0.005236333,0.00007551967,0.00004480943,0.00003015158,0.001695811,0.000006558694,0.0002384867],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02996418,"threshold_uncertainty_score":0.05957955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04153490928077576,"score_gpt":0.3493337837975727,"score_spread":0.3077988745167969,"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."}}