{"id":"W2564095444","doi":"10.1038/srep38707","title":"Lipidomic analysis enables prediction of clinical outcomes in burn patients","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Burn Injury Management and Outcomes","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; Sunnybrook Hospital; University of Toronto","funders":"National Institute of General Medical Sciences; Canadian Institutes of Health Research; National Institutes of Health","keywords":"Hypermetabolism; Medicine; Sepsis; Internal medicine; Burn injury; Prospective cohort study; Lipid metabolism; Inflammation; Cohort; Burn center; Lipid profile; Cohort study; Inflammatory response; Physiology; Gastroenterology; Surgery; Poison control; Emergency medicine; Cholesterol","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.000505524,0.0003233526,0.0004399799,0.001076379,0.0002764113,0.000691857,0.0001649264,0.0003464445,0.000973978],"category_scores_gemma":[0.0014454,0.0001304974,0.000261919,0.0008035436,0.0001779413,0.0003698637,0.0004580851,0.0004857787,0.0002306584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002626637,"about_ca_system_score_gemma":0.0002832124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001730071,"about_ca_topic_score_gemma":0.00188789,"domain_scores_codex":[0.9997547,0.00007318665,0.00003416135,0.00004673344,0.00004318659,0.00004798563],"domain_scores_gemma":[0.9995458,0.00009682791,0.0001737527,0.00003865016,0.00007566554,0.0000693015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009330921,0.00005074544,0.9859099,0.00002211587,0.00005903283,0.0001315765,0.00006116377,0.0002502647,0.005021721,0.00003665232,0.000118484,0.007405227],"study_design_scores_gemma":[0.000015121,0.0002541868,0.9943323,0.00002072039,0.00006242996,0.0003698707,0.0002915868,0.002223373,0.001894674,0.0002035718,0.0003216221,0.00001047315],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981982,0.0004045035,0.000516913,0.00008314026,0.000008094727,0.00001381339,0.0004020956,0.00001005817,0.0003631696],"genre_scores_gemma":[0.9987772,0.0002011443,0.0004604998,0.0000334669,0.00001059894,0.000009543798,0.0004003516,0.000002763432,0.000104409],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001730071,"threshold_uncertainty_score":0.003440022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03349341897234469,"score_gpt":0.3271070597957847,"score_spread":0.29361364082344,"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."}}