{"id":"W4410335200","doi":"10.18192/uojm.v15i1.6930","title":"Optimizing Cardiac Monitoring Utilization in the Emergency Department for Patients Awaiting In-Hospital Beds","year":2025,"lang":"en","type":"article","venue":"University of Ottawa Journal of Medicine","topic":"Healthcare Technology and Patient Monitoring","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Emergency department; Medicine; Medical emergency; Emergency medicine; Nursing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006764135,0.0002145608,0.0002757364,0.0007078643,0.0004983891,0.0006591515,0.0003503942,0.0002638796,0.001406458],"category_scores_gemma":[0.005083976,0.0001045438,0.0003089619,0.0005846379,0.0001342179,0.0004512104,0.0005377121,0.0005052574,0.0001784745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007318565,"about_ca_system_score_gemma":0.001600819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005309142,"about_ca_topic_score_gemma":0.01137747,"domain_scores_codex":[0.9993363,0.000229187,0.00011466,0.00006697794,0.000101441,0.0001514008],"domain_scores_gemma":[0.9971402,0.0004635712,0.001446896,0.00004857466,0.0003135793,0.0005873067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001126456,0.0001972389,0.9799094,0.0001093601,0.00002911778,0.0002166463,0.000162898,0.0001910388,0.0002316457,0.00003016599,0.001748898,0.0170609],"study_design_scores_gemma":[0.00002133711,0.0004142452,0.9952397,0.0001415508,0.00003391769,0.0005246022,0.001157401,0.0009450804,0.000271687,0.00005782648,0.001181738,0.00001079436],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944371,0.00120986,0.0004106282,0.001376969,0.00004473793,0.00009680705,0.0004424744,0.0000269319,0.001954618],"genre_scores_gemma":[0.9977264,0.0005866714,0.0008080222,0.0002708146,0.00007996148,0.00003582977,0.0003352276,0.000003229203,0.0001538752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005309142,"threshold_uncertainty_score":0.01055646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02665526454553577,"score_gpt":0.3056017687264863,"score_spread":0.2789465041809505,"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."}}