{"id":"W2082159108","doi":"10.3109/10903127.2013.811561","title":"Using Operations Research to Plan Improvement of the Transport of Critically Ill Patients","year":2013,"lang":"en","type":"article","venue":"Prehospital Emergency Care","topic":"Trauma and Emergency Care Studies","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Paul's Hospital; University of British Columbia","funders":"","keywords":"Medicine; Critically ill; Percentile; Standard deviation; Sensitivity (control systems); Statistics; Operations management; Operations research; Intensive care medicine; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008638956,0.000134035,0.000247562,0.00009181183,0.0001560539,0.00000241189,0.0001890065,0.00005540599,0.0006599261],"category_scores_gemma":[0.0003467728,0.00009396139,0.0001776831,0.00038962,0.0001019856,0.00008262634,0.0001004357,0.0001540853,0.0000117941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006285041,"about_ca_system_score_gemma":0.00009596739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002298906,"about_ca_topic_score_gemma":0.0003429467,"domain_scores_codex":[0.9982309,0.00002805824,0.0005337287,0.0002382648,0.0006556474,0.0003133492],"domain_scores_gemma":[0.9935327,0.000009456364,0.00002581194,0.0003799922,0.005929057,0.0001230257],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006392354,0.0007068658,0.879121,0.001139319,0.0002385293,0.000001457756,0.02940464,0.0003508055,0.07350711,0.0005053011,0.003946137,0.0110149],"study_design_scores_gemma":[0.0004347629,0.001097754,0.9704481,0.0001538379,0.00009234092,3.155562e-7,0.01138554,0.000040768,0.0158236,0.00006426308,0.0003126848,0.0001460791],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907103,0.0004111065,0.00005117417,0.0006464803,0.0007282498,0.001421809,0.0001167055,0.00001299446,0.005901201],"genre_scores_gemma":[0.9990407,0.0000493737,0.000454903,0.00008847314,0.00005942202,0.0001058976,0.00002062864,0.00001977533,0.0001608033],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09132704,"threshold_uncertainty_score":0.7225728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05541440090185737,"score_gpt":0.3537363124681422,"score_spread":0.2983219115662848,"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."}}