{"id":"W2032916871","doi":"10.1016/j.resuscitation.2009.12.008","title":"“Identifying the hospitalised patient in crisis”—A consensus conference on the afferent limb of Rapid Response Systems","year":2010,"lang":"en","type":"article","venue":"Resuscitation","topic":"Sepsis Diagnosis and Treatment","field":"Medicine","cited_by":372,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Canadian Patient Safety Institute","funders":"National Center for Research Resources","keywords":"Medicine; Modalities; Workload; Risk analysis (engineering); Intensive care medicine; Patient safety; Health care; Warning system; Medical emergency; Vital signs; Computer science; Surgery","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":[0.1717601,0.002061207,0.005372826,0.005278982,0.007410569,0.009261688,0.0150512,0.02954939,0.002513828],"category_scores_gemma":[0.1355547,0.00184024,0.005020576,0.00395664,0.01043934,0.008596874,0.01329913,0.04944443,0.001451873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01368634,"about_ca_system_score_gemma":0.08101386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01208762,"about_ca_topic_score_gemma":0.01857037,"domain_scores_codex":[0.9087377,0.04948102,0.0195969,0.003155136,0.01506669,0.003962632],"domain_scores_gemma":[0.8063294,0.09567177,0.01184152,0.003685112,0.06104365,0.02142853],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.000548781,0.0006131096,0.003332258,0.01449444,0.0005683099,0.001372862,0.007628286,0.002418266,0.001711164,0.02852007,0.5543206,0.3844719],"study_design_scores_gemma":[0.0004109061,0.0004570815,0.005305847,0.05744822,0.0005936848,0.002156535,0.01039085,0.002338248,0.001317891,0.02951306,0.8896858,0.0003819463],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.001713558,0.08457926,0.01593956,0.864311,0.02624855,0.001022539,0.0001548586,0.0001167542,0.005913936],"genre_scores_gemma":[0.08419511,0.2060453,0.1921953,0.4636908,0.04078481,0.004377452,0.001604731,0.000410194,0.00669615],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1717601,"threshold_uncertainty_score":0.9083651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1026633302798525,"score_gpt":0.3386737091942767,"score_spread":0.2360103789144242,"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."}}