{"id":"W122765791","doi":"10.1097/ta.0b013e318240507b","title":"Comparison of massive blood transfusion predictive models in the rural setting","year":2012,"lang":"en","type":"article","venue":"The Journal of Trauma: Injury, Infection, and Critical Care","topic":"Trauma, Hemostasis, Coagulopathy, Resuscitation","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"St Mary's Hospital Centre","funders":"National Institute of General Medical Sciences","keywords":"Medicine; Trauma center; Injury Severity Score; Major trauma; Blood transfusion; Receiver operating characteristic; Population; Emergency medicine; Surgery; Internal medicine; Retrospective cohort study; Injury prevention; Poison control","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001048,0.0001499431,0.0003605375,0.0001526632,0.0001875924,0.00001943795,0.00009275747,0.000113528,0.00001436485],"category_scores_gemma":[0.0002954918,0.00008812475,0.0001295307,0.0002382356,0.000236369,0.0003761973,0.00001411582,0.00062623,5.451215e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006469735,"about_ca_system_score_gemma":0.00005831409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001062843,"about_ca_topic_score_gemma":0.0000665695,"domain_scores_codex":[0.9981106,0.0004058746,0.0006316227,0.0000807157,0.0005123853,0.0002588071],"domain_scores_gemma":[0.998435,0.000549178,0.0001658609,0.0001441659,0.000582993,0.0001228596],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003192267,0.00189111,0.7391663,0.001106797,0.0002025935,0.00001255942,0.2031428,0.0006393762,0.007515088,0.002688364,0.000478464,0.03996439],"study_design_scores_gemma":[0.002764322,0.004054465,0.8683924,0.0006557647,0.001711437,0.0005879107,0.1048096,0.0007605047,0.01388632,0.002125666,0.00006462602,0.0001870321],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924725,0.002482735,0.002549665,0.001226311,0.000310549,0.000306691,0.00002117237,0.00001130149,0.0006191172],"genre_scores_gemma":[0.9991228,0.0002575526,0.0001309124,0.000110926,0.0003521255,0.000005200049,0.000004760094,0.00001415432,0.000001545083],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1292261,"threshold_uncertainty_score":0.3593623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02948704886468137,"score_gpt":0.350922872779235,"score_spread":0.3214358239145536,"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."}}