{"id":"W2089780222","doi":"10.1097/mlr.0b013e318242315b","title":"An Analysis of the New York University Emergency Department Algorithm’s Suitability for Use in Gauging Changes in ED Usage Patterns","year":2012,"lang":"en","type":"article","venue":"Medical Care","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Emergency department; Variety (cybernetics); Sensitivity (control systems); Computer science; Psychological intervention; Machine learning; Medicine; Operations research; Artificial intelligence; Data science; Data mining; Mathematics; Engineering; Psychiatry","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":[0.0003356742,0.0001015412,0.0003319093,0.0001293734,0.00004607726,0.000001196127,0.0001333291,0.00008315696,0.0005777231],"category_scores_gemma":[0.0002689438,0.00007275029,0.0001528781,0.000573198,0.00004221521,0.00006096943,0.00006821667,0.0001296303,2.905772e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001395217,"about_ca_system_score_gemma":0.00006550051,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002818962,"about_ca_topic_score_gemma":0.06215568,"domain_scores_codex":[0.9988956,0.0001054856,0.0002033345,0.0001845379,0.0003385701,0.0002724805],"domain_scores_gemma":[0.9993552,0.00007445751,0.00005100042,0.0002616837,0.00007288837,0.0001847795],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002776478,0.0001073313,0.9805612,0.0000802487,0.0001157607,0.000005300838,0.006329473,0.00000231436,0.000015828,0.00001180628,0.0004864243,0.01225656],"study_design_scores_gemma":[0.0005576237,0.0000702015,0.9848843,0.00006326862,0.0004881723,3.127575e-7,0.01141863,0.0003451737,0.0001616501,0.000002759013,0.001930672,0.0000772223],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960366,0.001599331,0.0006414699,0.0008120494,0.0003289299,0.0003435987,0.0001745493,0.00001087638,0.00005252506],"genre_scores_gemma":[0.9990783,0.0003460179,0.0001744123,0.0001131764,0.0001263019,0.000007004192,0.0001042168,0.000005689836,0.0000448794],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05933671,"threshold_uncertainty_score":0.9549575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03068225240376465,"score_gpt":0.303345886391145,"score_spread":0.2726636339873803,"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."}}