{"id":"W2588844730","doi":"10.21037/atm.2017.01.29","title":"Automated dynamic sepsis surveillance with routine data: opportunities and challenges","year":2017,"lang":"en","type":"letter","venue":"Annals of Translational Medicine","topic":"Sepsis Diagnosis and Treatment","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Workload; Critically ill; Intensive care unit; Health care; Intensive care medicine; Medicine; Risk analysis (engineering); Medical emergency; Sepsis; Computer science; Data science","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":[0.009997927,0.0005955118,0.001062621,0.001212848,0.001483326,0.004644826,0.002106891,0.01235581,0.002596405],"category_scores_gemma":[0.07700583,0.0005802996,0.0007853074,0.001263352,0.002504927,0.007442858,0.001799457,0.01645714,0.003666585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00236226,"about_ca_system_score_gemma":0.002409401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001774136,"about_ca_topic_score_gemma":0.00249553,"domain_scores_codex":[0.9907055,0.004557369,0.001234365,0.0009209513,0.002180338,0.0004013321],"domain_scores_gemma":[0.9240954,0.0536058,0.003097262,0.003474385,0.01273652,0.0029906],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002010261,0.0001189655,0.0131451,0.0005072874,0.00007993903,0.004781577,0.0007379201,0.0007898802,0.0008601422,0.008924156,0.6981989,0.2716551],"study_design_scores_gemma":[0.0002252413,0.0002831295,0.008546862,0.003090007,0.0001120963,0.01706079,0.002302496,0.01232474,0.001035728,0.09902716,0.855778,0.000213792],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.001043296,0.004522393,0.001408227,0.9876304,0.004001635,0.00001485267,0.00007575023,0.00007729247,0.001226212],"genre_scores_gemma":[0.05599464,0.02693407,0.01024667,0.7868226,0.1175748,0.0001523536,0.0004909873,0.0001335192,0.001650525],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.01235581,"threshold_uncertainty_score":0.05287468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.47505242587608,"score_gpt":0.4244262275554802,"score_spread":0.05062619832059978,"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."}}