{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.09402816,0.0002658112,0.004407778,0.001289935,0.0001723962,0.00003141894,0.00108458,0.0001274136,0.0004133887],"category_scores_gemma":[0.09550457,0.0001494771,0.0005869036,0.0007567887,0.0005119513,0.00009621908,0.0006600753,0.001337955,8.126532e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001723201,"about_ca_system_score_gemma":0.0009679651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007880278,"about_ca_topic_score_gemma":0.0002043981,"domain_scores_codex":[0.9663661,0.02774712,0.003586833,0.0003771874,0.001449173,0.0004735726],"domain_scores_gemma":[0.9237287,0.07248934,0.002986412,0.000328303,0.00005592734,0.0004113267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004375365,0.001218816,0.005656612,0.5561453,0.007201709,0.000119568,0.001412769,0.00000175004,8.934612e-8,0.006441505,0.001817572,0.4199406],"study_design_scores_gemma":[0.0006477817,0.001254379,0.001720256,0.04883494,0.002107348,0.0003851891,0.001639048,0.0001234215,1.313449e-8,0.02205626,0.920891,0.0003403507],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00006383526,0.9799049,0.002525211,0.01584467,0.00006193661,0.001370921,0.0002096084,0.000002922216,0.00001598179],"genre_scores_gemma":[0.0005424236,0.9952153,0.001645003,0.002302542,0.00006112429,0.0001451416,0.00006093632,0.00001370238,0.00001384212],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9190735,"threshold_uncertainty_score":0.9328887,"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."}}