{"id":"W7137942250","doi":"10.6084/m9.figshare.4320665.v1","title":"Additional file 4: Table S4. of To develop a regional ICU mortality prediction model during the first 24 h of ICU admission utilizing MODS and NEMS with six other independent variables from the Critical Care Information System (CCIS) Ontario, Canada","year":2016,"lang":"","type":"article","venue":"Figshare","topic":"Trauma and Emergency Care Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Logistic regression; Intensive care unit; Table (database); Multivariable calculus; Center (category theory); Life table; Set (abstract data type)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00169964,0.001108141,0.001160637,0.002238327,0.001048891,0.001375525,0.002217854,0.0006923691,0.8302968],"category_scores_gemma":[0.02944138,0.000734168,0.001364491,0.003726634,0.0002690802,0.001140184,0.0007636048,0.0009233781,0.1236034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001735341,"about_ca_system_score_gemma":0.003824002,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1088131,"about_ca_topic_score_gemma":0.1472887,"domain_scores_codex":[0.9994236,0.0001214677,0.00008652605,0.0001373692,0.0001056917,0.0001253962],"domain_scores_gemma":[0.983838,0.0120582,0.0005779836,0.0006889849,0.002453312,0.0003835876],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003806286,0.000102057,0.01120977,0.001700863,0.0001163386,0.00006938978,0.00008276635,0.001126017,0.00006003295,0.0003179792,0.9755256,0.009308454],"study_design_scores_gemma":[0.01234078,0.0005757529,0.2016237,0.006688217,0.001197323,0.0007633713,0.002231624,0.01582841,0.001525356,0.009704922,0.7471254,0.0003950529],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.0004299477,0.00001205703,0.000192556,0.00006027109,0.00001796429,0.00007138827,0.9984788,0.0001234917,0.0006134204],"genre_scores_gemma":[0.02518263,0.0001513308,0.005691291,0.0004051405,0.00009794223,0.002798195,0.9505481,0.001013416,0.01411196],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.891187,"threshold_uncertainty_score":0.242061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03667178312247119,"score_gpt":0.2339289387402425,"score_spread":0.1972571556177713,"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."}}