{"id":"W1966155603","doi":"10.1016/j.resuscitation.2012.11.019","title":"Modeling the impact of public access defibrillator range on public location cardiac arrest coverage","year":2012,"lang":"en","type":"article","venue":"Resuscitation","topic":"Cardiac Arrest and Resuscitation","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Michael's Hospital; Queen's University; University of Toronto","funders":"Institute of Circulatory and Respiratory Health; Heart and Stroke Foundation of Canada; National Heart, Lung, and Blood Institute; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; American Heart Association","keywords":"Medicine; Automated external defibrillator; First responder; Defibrillation; Medical emergency; Public access; Software deployment; Range (aeronautics); Public place; Emergency medical services; Retrospective cohort study; Emergency medicine; Cardiopulmonary resuscitation; Resuscitation; Cardiology; Internal medicine; Engineering; Library science; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001122623,0.0001848763,0.0003163088,0.0002806513,0.0001800285,0.0001184177,0.0001156844,0.0001243942,0.0000129088],"category_scores_gemma":[0.0009172196,0.0001209499,0.0003280652,0.0008297743,0.00007213723,0.0009288565,0.00003787415,0.0001734328,0.00004614206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003017713,"about_ca_system_score_gemma":0.0002634029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002133339,"about_ca_topic_score_gemma":0.000009265126,"domain_scores_codex":[0.9981726,0.0002506796,0.0003720773,0.0002105473,0.0005926092,0.0004014537],"domain_scores_gemma":[0.9983346,0.0002726121,0.0001831811,0.0004265313,0.0005635078,0.0002195925],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006893816,0.0004185397,0.9123518,0.0003751309,0.0007590345,0.000001182165,0.002978462,0.03766323,0.006286076,0.009229594,0.004602498,0.02464505],"study_design_scores_gemma":[0.001204806,0.0001267819,0.9776053,0.0001471953,0.0001435138,0.000001772074,0.0004069859,0.01869106,0.0002690408,0.0004325513,0.000741396,0.0002295577],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9850584,0.0008387844,0.004702618,0.0009379508,0.00194712,0.0007295575,0.00002259049,0.0000624746,0.005700503],"genre_scores_gemma":[0.9982502,0.0001814809,0.00005370741,0.00005879,0.001162448,0.00004362988,0.0001986679,0.00003277502,0.00001830641],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06525352,"threshold_uncertainty_score":0.4932193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05421702429887467,"score_gpt":0.337187421006587,"score_spread":0.2829703967077123,"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."}}