{"id":"W2615528965","doi":"10.2196/humanfactors.7567","title":"Iterative User Interface Design for Automated Sequential Organ Failure Assessment Score Calculator in Sepsis Detection","year":2017,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Sepsis Diagnosis and Treatment","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institutes of Health; Georgia Clinical and Translational Science Alliance","keywords":"Calculator; Computer science; Sepsis; Interface (matter); Reliability engineering; Medicine; Internal medicine; Engineering; Operating system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000133226,0.0002787692,0.0004006985,0.0001903711,0.0004259377,0.0002182557,0.0001407573,0.0001705275,0.0002252203],"category_scores_gemma":[0.00006342355,0.0002178585,0.000155538,0.00007404937,0.00006646987,0.0002507025,0.00005585331,0.0001756641,0.00001392044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000607926,"about_ca_system_score_gemma":0.0000765756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000194089,"about_ca_topic_score_gemma":0.0005396579,"domain_scores_codex":[0.9986728,0.00006676401,0.0003040674,0.0004165446,0.000235755,0.0003040856],"domain_scores_gemma":[0.9989716,0.0000743211,0.0002114849,0.0004780144,0.000126209,0.0001384014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001475928,0.001026443,0.9343946,0.0001106995,0.0004896862,0.00004895574,0.002252486,0.00009188825,0.05716076,0.0001254656,0.003604369,0.0005470796],"study_design_scores_gemma":[0.003152492,0.0008468387,0.8493071,0.0002241246,0.0001264067,0.000003820229,0.0002735866,0.001284007,0.1435001,0.00003100274,0.001030603,0.0002199287],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958521,0.00001226513,0.001284627,0.0002462424,0.000247926,0.002052286,0.00002634932,0.0001960396,0.00008215234],"genre_scores_gemma":[0.9981829,0.000001650867,0.0008256444,0.00005137896,0.00009766165,0.0005017495,0.00007014862,0.000046894,0.000221994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08633933,"threshold_uncertainty_score":0.8884011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1394203549545232,"score_gpt":0.4330433328665535,"score_spread":0.2936229779120303,"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."}}