{"id":"W2788017094","doi":"10.1017/s1049023x18000067","title":"Developing Public Health Initiatives through Understanding Motivations of the Audience at Mass-Gathering Events","year":2018,"lang":"en","type":"article","venue":"Prehospital and Disaster Medicine","topic":"Travel-related health issues","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Mass gathering; Attendance; Public relations; Public health; Event (particle physics); Target audience; Health promotion; Population; Mass media; Psychological intervention; Promotion (chess); Medicine; Psychology; Business; Advertising; Political science; Environmental health; Nursing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002894552,0.0001505261,0.0003187713,0.00006266302,0.0003367199,0.000004799041,0.00009725069,0.00005427038,0.00008374469],"category_scores_gemma":[0.0002821816,0.00009084149,0.00003016973,0.0003309312,0.00065378,0.0002643107,0.000122297,0.00014962,0.000005430195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002881708,"about_ca_system_score_gemma":0.000136005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005908781,"about_ca_topic_score_gemma":0.00002780738,"domain_scores_codex":[0.9986004,0.00006285893,0.000433699,0.0002440789,0.0003195312,0.0003394584],"domain_scores_gemma":[0.9992085,0.0001082736,0.000224239,0.0002128093,0.000089537,0.0001567185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008907467,0.0001136548,0.6711909,0.001010814,0.0001643433,0.000003098808,0.257048,5.627593e-7,0.001038249,0.06740554,0.0002732229,0.001662515],"study_design_scores_gemma":[0.002202083,0.001186101,0.9576527,0.003100166,0.00004462476,0.00003189398,0.02408778,0.00007481476,0.0003733511,0.00948396,0.001586085,0.0001764531],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9207918,0.001310317,0.01647549,0.05103756,0.0005262489,0.000592402,0.000007626325,0.0000496724,0.00920886],"genre_scores_gemma":[0.9962382,0.0002711906,0.001376769,0.001676926,0.0002282893,0.000010771,0.000006861844,0.00001655601,0.0001743918],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2864618,"threshold_uncertainty_score":0.3704408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1873741178909471,"score_gpt":0.3642796712336854,"score_spread":0.1769055533427383,"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."}}