{"id":"W2754600319","doi":"10.2196/mhealth.8296","title":"Improvements in Patient Acceptance by Hospitals Following the Introduction of a Smartphone App for the Emergency Medical Service System: A Population-Based Before-and-After Observational Study in Osaka City, Japan","year":2017,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medical emergency; Emergency medical services; Phone; Population; Observational study; Medicine; Emergency department; Service (business); Emergency medicine; Nursing; Business","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00099013,0.0004263759,0.0007157926,0.0009537608,0.0009135224,0.001143237,0.0005561599,0.0008955487,0.001153046],"category_scores_gemma":[0.003063018,0.0006338934,0.001368677,0.001133714,0.0005600698,0.001159968,0.001073902,0.001363093,0.0002628326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001152955,"about_ca_system_score_gemma":0.0009497196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01461428,"about_ca_topic_score_gemma":0.01803394,"domain_scores_codex":[0.9989016,0.0002213929,0.0001687254,0.0002368818,0.0002115711,0.0002597591],"domain_scores_gemma":[0.997075,0.0002794425,0.001416946,0.0001583447,0.0003747239,0.0006955067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001334535,0.0002058811,0.9980974,0.00002015788,0.00006440439,0.0001164339,0.000500704,0.00001258101,0.0001001223,0.000004832311,0.00008302308,0.0006610926],"study_design_scores_gemma":[0.00001090875,0.0003219788,0.9983727,0.00001086857,0.00004389102,0.00008785142,0.0009722583,0.00006349377,0.00002004713,0.000003600445,0.00008401689,0.00000842243],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995776,0.0001146105,0.00002931603,0.0000337548,0.000005274347,0.00002193599,0.0001067811,0.000001368405,0.0001094198],"genre_scores_gemma":[0.9994085,0.0001148696,0.00005083298,0.00007278939,0.00001140996,0.00004258907,0.0001960908,0.000001848556,0.000101065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01461428,"threshold_uncertainty_score":0.02905846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04033188853257298,"score_gpt":0.3762859529625186,"score_spread":0.3359540644299456,"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."}}