{"id":"W4405596239","doi":"10.2196/63557","title":"Characteristics of In-Flight Medical Emergencies on a Commercial Airline in Mainland China: Retrospective Study","year":2024,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Travel-related health issues","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China; Ruijin Hospital; Shanghai Municipal Health Commission","keywords":"IMes; Medicine; Incidence (geometry); Mainland China; Demography; Logistic regression; China; Retrospective cohort study; China mainland; Mortality rate; Geography; Surgery; Internal medicine; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002729954,0.0001944542,0.000859595,0.0004633116,0.00005861438,0.0000181152,0.00009401127,0.0001826979,0.0001037858],"category_scores_gemma":[0.0008323227,0.0001576247,0.00003637042,0.0008704236,0.00009596188,0.00006021332,0.00004337385,0.000881392,0.000009023408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002551844,"about_ca_system_score_gemma":0.001368651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008751856,"about_ca_topic_score_gemma":0.003591631,"domain_scores_codex":[0.9970843,0.0003636445,0.0009555577,0.0004198752,0.0005941509,0.0005825117],"domain_scores_gemma":[0.9987909,0.0001631511,0.0001119822,0.0002385879,0.00007574134,0.0006196104],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002410588,0.0007601981,0.9710764,0.0008392059,0.00001949788,0.0001781704,0.008412898,7.78528e-8,9.911735e-7,0.0007340159,0.0008905025,0.01684698],"study_design_scores_gemma":[0.001689048,0.001741624,0.9857494,0.0002883131,7.639321e-7,0.00002113276,0.000490799,0.0003729561,1.927912e-7,0.00002659917,0.009509551,0.0001095993],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.956292,0.001730549,0.00001062293,0.03963894,0.0004042134,0.001150298,0.00004172312,0.00006503456,0.0006666484],"genre_scores_gemma":[0.9965802,0.001832184,0.00002075879,0.001086334,0.0002251137,0.00007423134,0.00004508101,0.00002468162,0.0001113762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04028827,"threshold_uncertainty_score":0.6427748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02781994311606826,"score_gpt":0.3529950553493442,"score_spread":0.3251751122332759,"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."}}