{"id":"W3131515534","doi":"10.1017/s1049023x21000078","title":"Measuring the Masses: Understanding Health Outcomes Arising from Mass Gatherings, Reporting Gaps, and Recommendations (Paper 2)","year":2021,"lang":"en","type":"article","venue":"Prehospital and Disaster Medicine","topic":"Travel-related health issues","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Content (measure theory); Action (physics); Content analysis; Psychology; Computer science; Business; Sociology; Mathematics; Physics","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1476599,0.001116968,0.00121859,0.006479322,0.003799822,0.01114076,0.003549908,0.003659657,0.007163074],"category_scores_gemma":[0.3199693,0.0009232466,0.001790022,0.007222482,0.005257557,0.01798619,0.009808154,0.005078191,0.001028492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00749771,"about_ca_system_score_gemma":0.02362762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02012561,"about_ca_topic_score_gemma":0.01753011,"domain_scores_codex":[0.9247242,0.0538269,0.007023061,0.003959156,0.008328655,0.002138047],"domain_scores_gemma":[0.7713634,0.1603338,0.03120039,0.01056765,0.02275219,0.003782692],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002245794,0.0002688933,0.1809186,0.007109859,0.0005624022,0.0003043096,0.06643173,0.0009700544,0.0002426334,0.04913272,0.1128382,0.580996],"study_design_scores_gemma":[0.000187075,0.0008977166,0.1916088,0.05914416,0.001065663,0.0009999883,0.1561893,0.005250841,0.002247059,0.2399704,0.3420688,0.0003702203],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.08603998,0.04811662,0.09080501,0.7177793,0.005901009,0.004992483,0.00835875,0.0004104914,0.03759637],"genre_scores_gemma":[0.6325107,0.05234571,0.2092373,0.07941058,0.005546837,0.01043763,0.005280826,0.0002234437,0.005007103],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8523402,"threshold_uncertainty_score":0.7809093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1134244516700523,"score_gpt":0.3423067474396284,"score_spread":0.2288822957695761,"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."}}