{"id":"W2789433208","doi":"10.1016/j.resuscitation.2018.02.010","title":"Automated video surveillance and machine learning: Leveraging existing infrastructure for cardiac arrest detection and emergency response activation","year":2018,"lang":"en","type":"letter","venue":"Resuscitation","topic":"Cardiac Arrest and Resuscitation","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Royal Alexandra Hospital; University of Alberta","funders":"","keywords":"Medicine; Medical emergency; Terrorism; Beijing; Artificial intelligence; Computer science; Political science","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":[0.00219946,0.0003638739,0.0004586971,0.0006776565,0.0005999926,0.002150957,0.00108836,0.005670895,0.003885811],"category_scores_gemma":[0.01925142,0.0003109273,0.000427488,0.0003713513,0.0006868741,0.002733022,0.001206009,0.007306003,0.00287109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008138651,"about_ca_system_score_gemma":0.00124339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002195601,"about_ca_topic_score_gemma":0.005916367,"domain_scores_codex":[0.9982455,0.000689029,0.0001605256,0.0001801954,0.0005440147,0.000180752],"domain_scores_gemma":[0.986585,0.009483846,0.0005613909,0.0006815464,0.002075678,0.0006125222],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003831907,0.0003372725,0.01345675,0.000205101,0.00008503343,0.003175247,0.0003098597,0.002470374,0.006384342,0.007974242,0.4309781,0.5342405],"study_design_scores_gemma":[0.0003053974,0.000849598,0.02088657,0.0008244767,0.0001683211,0.01060409,0.001911864,0.137247,0.01396186,0.09441849,0.718623,0.0001993228],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02156065,0.004744629,0.07267255,0.8673827,0.01016713,0.0001717596,0.0005160286,0.001325718,0.02145887],"genre_scores_gemma":[0.5831255,0.01087925,0.1053193,0.2273117,0.05583002,0.0003627788,0.001122324,0.0002772644,0.01577195],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005670895,"threshold_uncertainty_score":0.0129993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01998424528879153,"score_gpt":0.2848154483688827,"score_spread":0.2648312030800911,"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."}}