{"id":"W4283828597","doi":"10.3390/ijerph19148267","title":"Methods Used in the Spatial and Spatiotemporal Analysis of COVID-19 Epidemiology: A Systematic Review","year":2022,"lang":"en","type":"review","venue":"International Journal of Environmental Research and Public Health","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Spatial epidemiology; Coronavirus disease 2019 (COVID-19); Bayesian probability; Frequentist inference; Scopus; MEDLINE; Geography; Epidemiology; Computer science; Bayesian inference; Disease; Medicine; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.03420005,0.002439059,0.01065213,0.02589056,0.001105647,0.005115583,0.003114338,0.002579827,0.005716831],"category_scores_gemma":[0.1423483,0.001619251,0.01002108,0.02494998,0.001642483,0.005121455,0.002991074,0.001856585,0.0006051481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006410302,"about_ca_system_score_gemma":0.02467487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008403989,"about_ca_topic_score_gemma":0.02294841,"domain_scores_codex":[0.9618366,0.01462215,0.01590962,0.002150448,0.004952501,0.0005286359],"domain_scores_gemma":[0.8890074,0.0869654,0.01477298,0.002436848,0.006353027,0.0004643069],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.00006460983,0.000009789788,0.0006750694,0.9489645,0.007146993,0.0000674097,0.0002101247,0.0001655064,0.00008945831,0.0008695704,0.001335451,0.04040157],"study_design_scores_gemma":[0.00009817142,0.00006050041,0.001637899,0.9465604,0.03026767,0.0001930511,0.0002662965,0.0001448872,0.0001264568,0.00112984,0.0194754,0.00003932435],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003712714,0.995479,0.001448144,0.0005281757,0.0001643902,0.001103268,0.0006158839,0.00001718452,0.0002725767],"genre_scores_gemma":[0.0091204,0.9802546,0.00571809,0.0006032754,0.0001027027,0.003573295,0.0004706594,0.00001439535,0.0001424927],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.03420005,"threshold_uncertainty_score":0.1808693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.759314208239522,"score_gpt":0.6578560577352095,"score_spread":0.1014581505043125,"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."}}