{"id":"W2605965508","doi":"10.1017/s1049023x17003880","title":"Mass Gathering Medicine Tabletop Game - A Systems Approach to a Major Planned Event, Health Services Planning","year":2017,"lang":"en","type":"article","venue":"Prehospital and Disaster Medicine","topic":"Conferences and Exhibitions Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Event (particle physics); Action (physics); Computer science; Mass gathering; Multimedia; Medicine; 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":[0.0008118617,0.0001783247,0.0003836757,0.00009359258,0.0009295528,0.0001962603,0.0003926812,0.00004601476,0.0000697473],"category_scores_gemma":[0.00005049664,0.0001276563,0.00002509424,0.00009154854,0.0003078281,0.000277259,0.0001632458,0.00009517774,0.00001029432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004846777,"about_ca_system_score_gemma":0.0000314699,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01683989,"about_ca_topic_score_gemma":0.0004938736,"domain_scores_codex":[0.9983623,0.00007116292,0.0003167053,0.0003711146,0.0004381018,0.0004405986],"domain_scores_gemma":[0.9989666,0.00003882052,0.0002161757,0.0003354416,0.00004538755,0.0003975877],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002177295,0.0002199834,0.05226113,0.002445342,0.0002025326,0.00003547408,0.8361838,0.0001893529,0.00009615464,0.07900234,0.007453853,0.02169227],"study_design_scores_gemma":[0.00382067,0.002249553,0.05769242,0.008213869,0.000142497,0.00001047167,0.756486,0.004514637,0.000001240526,0.005260207,0.1608356,0.0007728025],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4965207,0.007802591,0.01316677,0.06142605,0.00227233,0.002555743,0.00003026117,0.0002271434,0.4159985],"genre_scores_gemma":[0.9947453,0.0001248543,0.0001114962,0.0006835535,0.000925473,0.00008331399,0.00001758189,0.00001159218,0.003296811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4982246,"threshold_uncertainty_score":0.9897071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03730700155497165,"score_gpt":0.334076270182243,"score_spread":0.2967692686272714,"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."}}