{"id":"W1607397681","doi":"10.1186/s13054-015-0969-7","title":"Shedding metabo‘light’ on the search for sepsis biomarkers","year":2015,"lang":"en","type":"letter","venue":"Critical Care","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Michael's Hospital","funders":"","keywords":"Medicine; Sepsis; Biomarker; Intensive care medicine; Inflammation; Systemic inflammation; Critical illness; Severe sepsis; Bioinformatics; Presentation (obstetrics); Immunology; Critically ill; Surgery; Septic shock","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00703697,0.001107375,0.002008027,0.001181266,0.002265872,0.004118402,0.00189076,0.02521823,0.003277776],"category_scores_gemma":[0.03145121,0.0006422327,0.001335529,0.0006691738,0.004688061,0.007269347,0.002152521,0.04430919,0.004187997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00249616,"about_ca_system_score_gemma":0.001821158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008622478,"about_ca_topic_score_gemma":0.00109467,"domain_scores_codex":[0.9950179,0.00180519,0.0007142083,0.0005475694,0.001576949,0.0003382023],"domain_scores_gemma":[0.9786807,0.0135158,0.001049731,0.0008565916,0.004008354,0.001888788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001823727,0.00008510586,0.0009100591,0.0002971867,0.00005443732,0.003368102,0.0002055691,0.0000885519,0.001033602,0.004226997,0.9475044,0.04204366],"study_design_scores_gemma":[0.0002405032,0.0003140596,0.001813214,0.001027455,0.00008645086,0.009551824,0.0006201745,0.0007551536,0.001186109,0.02933739,0.954922,0.0001456694],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"editorial","genre_scores_codex":[0.0004661356,0.01283797,0.0003868939,0.9408861,0.04462278,0.00001156766,0.00003788262,0.00005451645,0.0006961252],"genre_scores_gemma":[0.003912687,0.01000566,0.000705114,0.8130723,0.1705629,0.00002811438,0.00003165796,0.00003280688,0.001648737],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.02521823,"threshold_uncertainty_score":0.03721547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04174047258284117,"score_gpt":0.3302869909278425,"score_spread":0.2885465183450013,"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."}}