{"id":"W2904824750","doi":"10.1101/491712","title":"“Multimorbidity states with high sepsis-related deaths: a data-driven analysis in critical care”","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Michael's Hospital","funders":"","keywords":"Medicine; Health care; Latent class model; Demographics; Disease; Comorbidity; Population; Sepsis; Multimorbidity; Intensive care medicine; Demography; Internal medicine; Environmental health","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":[0.009317677,0.0004565415,0.0005155838,0.001268482,0.0003390427,0.001066328,0.000758636,0.0007326888,0.001439941],"category_scores_gemma":[0.02289664,0.0002253211,0.001716964,0.00114399,0.0004440751,0.0004381059,0.001114164,0.001140397,0.0002516288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007443205,"about_ca_system_score_gemma":0.001178435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007676851,"about_ca_topic_score_gemma":0.006839096,"domain_scores_codex":[0.9963201,0.00266278,0.0001636312,0.0004985732,0.0001899231,0.0001649895],"domain_scores_gemma":[0.9848985,0.01115827,0.001392348,0.001321404,0.0006706531,0.0005588498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001208239,0.0003803995,0.915379,0.0002729873,0.001598802,0.000244014,0.0002416606,0.03896362,0.0004827926,0.002810024,0.01200817,0.02641021],"study_design_scores_gemma":[0.0001370418,0.0004458928,0.469211,0.000194188,0.0004770152,0.0003702135,0.0004036992,0.5109205,0.0008939051,0.01083059,0.006043258,0.0000726381],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9593568,0.0009314668,0.02024364,0.003370856,0.000102952,0.0001780209,0.01497664,0.0002604064,0.0005792471],"genre_scores_gemma":[0.9763531,0.0001295355,0.01032321,0.0002819306,0.00005694028,0.0001075023,0.0124292,0.00002925611,0.0002893246],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009317677,"threshold_uncertainty_score":0.04927719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04356312005008174,"score_gpt":0.3181482970476027,"score_spread":0.274585176997521,"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."}}