{"id":"W2162863739","doi":"10.1186/cc11667","title":"Identification of sepsis subtypes in critically ill adults using gene expression profiling","year":2012,"lang":"en","type":"article","venue":"Critical Care","topic":"Sepsis Diagnosis and Treatment","field":"Medicine","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Critically ill; Sepsis; Gene expression profiling; Profiling (computer programming); Intensive care medicine; Severe sepsis; Identification (biology); Bioinformatics; Gene; Computational biology; Gene expression; Internal medicine; Septic shock; Genetics; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0001111324,0.0001025396,0.0002278856,0.00008609047,0.00003737697,0.000009619546,0.00003916849,0.00009539638,0.0000760305],"category_scores_gemma":[0.001547226,0.00008707274,0.00007664361,0.0001200624,0.00007547542,0.0001182995,0.00002879831,0.00008729516,0.00001376259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001099981,"about_ca_system_score_gemma":0.00003287331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002445988,"about_ca_topic_score_gemma":0.000002500401,"domain_scores_codex":[0.9989624,0.00004557489,0.0003324084,0.0001927208,0.0002002896,0.0002665963],"domain_scores_gemma":[0.9987497,0.0001655878,0.00002511941,0.0002160316,0.0006870505,0.0001565055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001274195,0.0009193538,0.7228827,0.0009077854,0.00001357855,0.00002197599,0.001317921,0.000003822133,0.2701678,0.001735627,0.00003216281,0.001869793],"study_design_scores_gemma":[0.0006556686,0.00009211064,0.1351,0.000507306,0.0001379246,0.00001194812,0.003020182,0.0002346832,0.8600355,0.00008083932,0.00002454499,0.00009934102],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950578,0.003471849,0.0002372907,0.0005316065,0.0001593516,0.0002532481,0.00002599114,0.00002047396,0.0002424331],"genre_scores_gemma":[0.9934714,0.00002128547,0.005973428,0.0003243893,0.0001155748,0.00003231146,0.00004088301,0.00001678961,0.000003879793],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5898677,"threshold_uncertainty_score":0.3550723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08264240219981202,"score_gpt":0.3916860741802507,"score_spread":0.3090436719804387,"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."}}