{"id":"W3039208487","doi":"10.1007/978-3-030-85053-1_1","title":"Diverse Local Epidemics Reveal the Distinct Effects of Population Density, Demographics, Climate, Depletion of Susceptibles, and Intervention in the First Wave of COVID-19 in the United States","year":2021,"lang":"en","type":"preprint","venue":"Fields Institute communications","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Perimeter Institute; University of Waterloo","funders":"","keywords":"Population; Pandemic; Outbreak; Demography; Geography; Social distance; Psychological intervention; Herd immunity; Metropolitan area; Population density; Intervention (counseling); Coronavirus disease 2019 (COVID-19); Medicine; Disease; Virology; Sociology; Infectious disease (medical specialty)","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":[0.001976125,0.0002198016,0.0003587421,0.0007727782,0.0005432177,0.001024498,0.0004455691,0.0004950464,0.002984357],"category_scores_gemma":[0.006068743,0.0002093668,0.000523057,0.0009783533,0.0005649547,0.0007793193,0.001454262,0.00113047,0.0002124255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006555189,"about_ca_system_score_gemma":0.0008177735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03945484,"about_ca_topic_score_gemma":0.05275264,"domain_scores_codex":[0.9993494,0.000332652,0.00001677755,0.0000884743,0.0000541298,0.0001585439],"domain_scores_gemma":[0.9975095,0.001111086,0.0005567258,0.0002906598,0.0002156147,0.0003164741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001150986,0.0005372081,0.9405276,0.00008656995,0.0003124391,0.0002141401,0.001713538,0.006330882,0.002312234,0.007479868,0.00932333,0.0300113],"study_design_scores_gemma":[0.00003489575,0.00008108655,0.986187,0.00002134962,0.00007319798,0.0000604076,0.002423127,0.007387335,0.0002480013,0.002840738,0.0006280496,0.00001487151],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996944,0.0001687809,0.000430674,0.0009126824,0.00000696729,0.000007284221,0.0005173124,0.00001699235,0.0009952562],"genre_scores_gemma":[0.9990544,0.00008919257,0.0001753144,0.00008419943,0.000006548387,0.000005782597,0.0003161473,0.000004217892,0.0002641054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03945484,"threshold_uncertainty_score":0.07845038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2328722733484097,"score_gpt":0.4171805602095008,"score_spread":0.1843082868610912,"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."}}