{"id":"W3004248899","doi":"10.1016/j.jbiotec.2020.01.013","title":"Evaluation of host-based molecular markers for the early detection of human sepsis","year":2020,"lang":"en","type":"article","venue":"Journal of Biotechnology","topic":"Bacterial Identification and Susceptibility Testing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"Defence Research and Development Canada","funders":"Bundesministerium für Digitalisierung und Wirtschaftsstandort; Steirische Wirtschaftsförderungsgesellschaft; Österreichische Forschungsförderungsgesellschaft; Austrian Science Fund","keywords":"Sepsis; Primer (cosmetics); Polymerase chain reaction; Nucleic acid; Molecular diagnostics; Biology; DNA; Host (biology); Computational biology; Medicine; Immunology; Bioinformatics; Genetics; Gene; Chemistry","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":[0.0009576783,0.00005547863,0.0001262496,0.00005797494,0.00003403153,0.000005568153,0.0001792213,0.0001763039,0.00000864533],"category_scores_gemma":[0.001090771,0.00004469935,0.0001274831,0.0001145462,0.00009739307,0.000002951252,0.00002309668,0.0000831021,1.977599e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001004074,"about_ca_system_score_gemma":0.00007605015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009732169,"about_ca_topic_score_gemma":0.00001184002,"domain_scores_codex":[0.9992207,0.00009437749,0.0003591809,0.00009820651,0.0001619301,0.00006560479],"domain_scores_gemma":[0.9987642,0.00002539746,0.0004885687,0.0001673696,0.0005338482,0.00002063621],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001100414,0.00002426903,0.0001947262,0.00001807318,0.00006989641,1.211291e-7,0.00002040405,0.00006901157,0.9895323,0.00002493784,0.00002677431,0.009909432],"study_design_scores_gemma":[0.0006331569,0.001033962,0.005164686,0.000009372018,0.0001371141,0.000002426037,0.0001042474,0.001037303,0.9914833,0.00006128082,0.0002936121,0.00003948763],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9765062,0.0002230376,0.02125643,0.001727233,0.00008252503,0.0001851517,0.000005935242,0.000003788525,0.000009675882],"genre_scores_gemma":[0.9992462,0.00001060958,0.0006168766,0.00006784706,0.00004258475,0.000004204181,0.000003160304,0.000006802002,0.000001739786],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02273996,"threshold_uncertainty_score":0.1822787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03427118848794188,"score_gpt":0.2972511072542879,"score_spread":0.262979918766346,"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."}}