{"id":"W2914797821","doi":"10.1371/journal.pone.0211274","title":"Determining predictors of sepsis at triage among children under 5 years of age in resource-limited settings: A modified Delphi process","year":2019,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Delphi Technique in Research","field":"Social Sciences","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"","keywords":"Triage; Delphi method; Guideline; Medicine; Health care; Delphi; Sepsis; Resource (disambiguation); Computer science; Medical emergency; Artificial intelligence; Surgery; Pathology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001511195,0.0001104452,0.0003942723,0.0003772588,0.00006109237,0.00002222547,0.0005698597,0.0002051179,0.00007941326],"category_scores_gemma":[0.001043556,0.0001246336,0.00006863311,0.0008769721,0.0003593917,0.0001571455,0.0001769368,0.0002542916,0.000007444162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001513924,"about_ca_system_score_gemma":0.0001093511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005690639,"about_ca_topic_score_gemma":0.0006079148,"domain_scores_codex":[0.9973652,0.00029173,0.0004658391,0.0003038768,0.001171718,0.0004015834],"domain_scores_gemma":[0.9986864,0.0004860123,0.0002770236,0.000332706,0.000119773,0.00009804224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001194329,0.0006699465,0.9661569,0.000199599,0.0001529081,0.00001074043,0.02149737,0.000154275,0.01038837,0.00005785398,0.0001340522,0.0004585684],"study_design_scores_gemma":[0.001857413,0.0003147939,0.9477654,0.001699914,0.0001016812,5.015776e-7,0.007926804,0.001017587,0.03822574,0.0006543105,0.00002529767,0.0004106359],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.993654,0.00002174073,0.000004532503,0.0001485267,0.00001160103,0.001161664,0.00001845255,0.00009045667,0.004889026],"genre_scores_gemma":[0.9990252,0.00001968442,0.0003391663,0.00003154343,0.00003584565,0.00005550489,0.00001173355,0.00002790706,0.0004533623],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02783737,"threshold_uncertainty_score":0.5082411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09306787455092493,"score_gpt":0.3478199856754676,"score_spread":0.2547521111245427,"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."}}