{"id":"W2591892707","doi":"10.1161/circulationaha.116.026318","title":"Optimizing a Drone Network to Deliver Automated External Defibrillators","year":2017,"lang":"en","type":"article","venue":"Circulation","topic":"Cardiac Arrest and Resuscitation","field":"Medicine","cited_by":269,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Sunnybrook Hospital; Institute for Christian Studies; University of Toronto; St. Michael's Hospital","funders":"National Heart, Lung, and Blood Institute; Hospital for Sick Children; Scheme for Promotion of Academic and Research Collaboration; University of Toronto","keywords":"Drone; Medicine; Automated external defibrillator; Defibrillation; Medical emergency; Percentile; Queueing theory; Emergency medicine; Cardiopulmonary resuscitation; Computer science; Cardiology; Statistics; Resuscitation; Computer network","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0006188809,0.0009155758,0.0003954459,0.0004685612,0.0003893978,0.0008376397,0.0008150573,0.0005781416,0.001986662],"category_scores_gemma":[0.001946254,0.0003361534,0.0005050525,0.0003741916,0.0004473587,0.0008758156,0.0006744251,0.0005066309,0.0001758133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004090176,"about_ca_system_score_gemma":0.002443772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05363205,"about_ca_topic_score_gemma":0.04489498,"domain_scores_codex":[0.9996138,0.0001095082,0.00001100317,0.00009537498,0.0000470397,0.0001233102],"domain_scores_gemma":[0.9991104,0.0003813161,0.0002020995,0.00003972814,0.0001661888,0.0001002999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004356891,0.00003078449,0.002303941,0.00001735637,0.00001515766,0.00002152159,0.00001060959,0.9949,0.0006102378,0.0002903917,0.0001407553,0.001615688],"study_design_scores_gemma":[0.00001909291,0.0001703431,0.002245343,0.000005127273,0.0000283289,0.0000148465,0.00007792659,0.996343,0.000484625,0.0003365689,0.0002691634,0.000005731004],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8944197,0.0002901362,0.09711283,0.0004886636,0.00003970046,0.0002950998,0.000594251,0.0002463832,0.006513175],"genre_scores_gemma":[0.9892741,0.0001227025,0.009085055,0.00003238531,0.00000538267,0.00007659476,0.0001622189,0.00001455402,0.001226894],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05363205,"threshold_uncertainty_score":0.1066397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01892802956071863,"score_gpt":0.2956781210577687,"score_spread":0.27675009149705,"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."}}