{"id":"W4324319686","doi":"10.1016/j.apgeog.2023.102922","title":"Identification of priority areas for public-access automated external defibrillators (AEDs) in metropolitan areas: A case study in Hangzhou, China","year":2023,"lang":"en","type":"article","venue":"Applied Geography","topic":"Cardiac Arrest and Resuscitation","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"China Scholarship Council; National Natural Science Foundation of China","keywords":"Geocoding; Metropolitan area; China; Geographic information system; Geography; Identification (biology); Environmental health; Environmental planning; Medical emergency; Medicine; Cartography","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":[0.0003822504,0.000391174,0.0002655321,0.001552393,0.002025957,0.0007819035,0.0009222979,0.0007995341,0.001797699],"category_scores_gemma":[0.001312724,0.0002528356,0.0003810559,0.002105892,0.001013987,0.000535103,0.001234723,0.0003654966,0.00007698429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003459599,"about_ca_system_score_gemma":0.00381471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1454798,"about_ca_topic_score_gemma":0.2498458,"domain_scores_codex":[0.9995871,0.00008806479,0.00003523964,0.00005623674,0.00005564313,0.0001776449],"domain_scores_gemma":[0.9992877,0.0001599327,0.0002080855,0.00003533319,0.0001181206,0.0001907846],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007985417,0.0001996079,0.9147141,0.0001853983,0.00007086653,0.05782623,0.01179618,0.000992629,0.001623374,0.001550374,0.00153784,0.009423529],"study_design_scores_gemma":[0.00002512025,0.0001887985,0.8854988,0.0001684408,0.0001801519,0.01644376,0.08541809,0.00598052,0.0007557083,0.00104993,0.004231298,0.00005943267],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984102,0.0001444249,0.0001718893,0.0003116022,0.000005838998,0.00003738065,0.00008125178,0.000005647694,0.0008316708],"genre_scores_gemma":[0.9992942,0.0001205899,0.0002008795,0.00003351998,0.000005150234,0.00001149802,0.00005436892,9.988994e-7,0.0002787173],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1454798,"threshold_uncertainty_score":0.289266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01955726095571787,"score_gpt":0.3266169766417306,"score_spread":0.3070597156860128,"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."}}