{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001288895,0.0000761439,0.0001409246,0.00004921138,0.0003061274,0.00007210088,0.00004027098,0.00006395223,0.00001647483],"category_scores_gemma":[0.00008518871,0.00007282859,0.0000708855,0.00006069299,0.00002249933,0.0001329689,0.00003053404,0.00004963562,0.0001083564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007274234,"about_ca_system_score_gemma":0.0000209553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004082092,"about_ca_topic_score_gemma":0.000005547118,"domain_scores_codex":[0.9993536,0.0000151615,0.0001349136,0.0001596641,0.0001773347,0.0001592694],"domain_scores_gemma":[0.9994076,0.00001509499,0.00008910251,0.0002943725,0.00008450619,0.0001092548],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001053847,0.00001308096,0.9088207,0.00003060884,0.0000550822,0.00002028024,0.0004969796,0.0512937,0.01748986,0.0003044377,0.001653938,0.01971593],"study_design_scores_gemma":[0.0004649865,0.000008495591,0.9594197,0.0001466836,0.000053186,0.00000895654,0.00001255881,0.03899911,0.0001701987,0.00009959599,0.0005322814,0.00008420547],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881274,0.0001080153,0.007019539,0.0002362287,0.001043503,0.0002633573,7.951585e-7,0.0001851413,0.003016013],"genre_scores_gemma":[0.9945551,0.000005993848,0.004404897,0.0001209762,0.0008551182,0.000006102953,0.00001441661,0.00001543781,0.00002202067],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05059901,"threshold_uncertainty_score":0.2969864,"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."}}