{"id":"W4293244589","doi":"10.1063/5.0089347","title":"Analysis of overdispersion in airborne transmission of COVID-19","year":2022,"lang":"en","type":"article","venue":"Physics of Fluids","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fields Institute for Research in Mathematical Sciences; University of Toronto","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Overdispersion; Coronavirus disease 2019 (COVID-19); Transmission (telecommunications); Outbreak; Occupancy; Airborne transmission; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Infectious disease (medical specialty); Pandemic; Statistics; Biology; Medicine; Ecology; Computer science; Mathematics; Disease; Virology; Count data; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008895723,0.0001140738,0.0008388108,0.0001663871,0.00005525299,8.004642e-7,0.000239551,0.0000343475,0.0002606374],"category_scores_gemma":[0.0009004339,0.00009829964,0.0003830993,0.001398026,0.0001084072,0.00003503857,0.0002258545,0.0001213636,3.024129e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001392151,"about_ca_system_score_gemma":0.00006273871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005470008,"about_ca_topic_score_gemma":0.00001390344,"domain_scores_codex":[0.9984266,0.0002302745,0.0006069833,0.0002121592,0.0003812561,0.000142703],"domain_scores_gemma":[0.9972737,0.002059808,0.0002540038,0.0003048404,0.00005359968,0.00005399335],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001372178,0.007275559,0.2805394,0.004611695,0.004222488,0.00001573662,0.02623817,0.1483714,0.2056686,0.2861635,0.00675974,0.02876156],"study_design_scores_gemma":[0.003545126,0.001328617,0.102192,0.0001315106,0.003406082,5.475379e-7,0.003052469,0.09975032,0.02640963,0.7533667,0.006045247,0.000771753],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9550094,0.0005450784,0.04259465,0.001033341,0.0000266077,0.0002374498,0.0001369411,0.00002390202,0.0003926491],"genre_scores_gemma":[0.9981669,0.00009444841,0.001534436,0.0001430125,0.000009084335,0.0000144962,0.0000138141,0.000007800408,0.00001595943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4672032,"threshold_uncertainty_score":0.4008543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1468268272302311,"score_gpt":0.4073824945966064,"score_spread":0.2605556673663753,"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."}}