{"id":"W3164429803","doi":"10.2196/29986","title":"Ambulatory Risk Models for the Long-Term Prevention of Sepsis: Retrospective Study","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Sepsis Diagnosis and Treatment","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Washington Research Foundation","keywords":"Medicine; Sepsis; Interpretability; Intensive care medicine; Ambulatory; Emergency medicine; Medical record; Receiver operating characteristic; Framingham Risk Score; Internal medicine; Machine learning; Computer science; Disease","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01436629,0.0007999776,0.0006810715,0.001281349,0.0003975292,0.001155475,0.001176699,0.0006465045,0.002484581],"category_scores_gemma":[0.03157268,0.0004343925,0.001571555,0.001407478,0.0002862708,0.0008553243,0.0009017935,0.001748536,0.0006055629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009416981,"about_ca_system_score_gemma":0.001007124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0154001,"about_ca_topic_score_gemma":0.007790135,"domain_scores_codex":[0.9957641,0.002998343,0.0002367937,0.0004964697,0.0003120876,0.0001920975],"domain_scores_gemma":[0.9693446,0.02219504,0.003123273,0.002783959,0.001727311,0.0008258736],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001469923,0.0008853124,0.9127784,0.00009327717,0.001630543,0.0002233974,0.0002011015,0.05797387,0.0001180413,0.0009437606,0.003396581,0.02028578],"study_design_scores_gemma":[0.0002701866,0.001251836,0.3049136,0.0001266628,0.0006548495,0.0005459187,0.0003618337,0.6863933,0.0002679139,0.002538468,0.00261839,0.00005688739],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9816605,0.00113527,0.01281376,0.0004600855,0.0000519568,0.0001060936,0.002659809,0.0001397632,0.0009726856],"genre_scores_gemma":[0.9932384,0.0002670206,0.003763201,0.00005479807,0.00003948874,0.00005609372,0.00225227,0.00002916884,0.0002994778],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0154001,"threshold_uncertainty_score":0.07597709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0665638722546908,"score_gpt":0.3824811366024926,"score_spread":0.3159172643478018,"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."}}