{"id":"W3212636283","doi":"10.1186/s12889-021-12080-1","title":"Quantifying contact patterns in response to COVID-19 public health measures in Canada","year":2021,"lang":"en","type":"article","venue":"BMC Public Health","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto; University of Guelph","funders":"Social Sciences and Humanities Research Council of Canada; Canadian Institutes of Health Research; Canada Research Chairs; Public Health Agency; Public Health Agency of Canada; University of Guelph","keywords":"Medicine; Biostatistics; Public health; Residence; Demography; Epidemiology; Coronavirus disease 2019 (COVID-19); Pandemic; Contact tracing; Population; Environmental health; Cross-sectional study; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.02453827,0.0003635572,0.001421997,0.0004702401,0.0003296582,0.0001128528,0.0004985787,0.0001187007,0.0001682429],"category_scores_gemma":[0.1478122,0.0003318918,0.0001048452,0.001690752,0.00003092405,0.0001746567,0.0004058987,0.0006145025,0.00001255054],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.02146532,"about_ca_system_score_gemma":0.08464998,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9438002,"about_ca_topic_score_gemma":0.9988541,"domain_scores_codex":[0.9845504,0.009045759,0.002112729,0.001055158,0.0009055383,0.002330484],"domain_scores_gemma":[0.9810838,0.01512223,0.0004864034,0.0008443728,0.0001906748,0.002272549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001013027,0.0002533983,0.9647967,0.001011812,0.00002032235,0.000108355,0.003027207,0.0000422423,0.000007323187,0.007937836,0.01826932,0.004424168],"study_design_scores_gemma":[0.001213227,0.0001512503,0.7988279,0.0001511032,0.000001296976,0.00001498825,0.005372699,0.0001838506,0.00000119896,0.001186489,0.1925467,0.0003492299],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5331486,0.000797901,0.01594131,0.4487062,0.0002243208,0.0009069199,0.0001149136,0.0001109902,0.00004873715],"genre_scores_gemma":[0.8892796,0.00020543,0.002546679,0.1076304,0.00005466165,0.0001749797,0.0000221703,0.0000353457,0.00005070902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3561309,"threshold_uncertainty_score":0.9999133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6310748810680801,"score_gpt":0.4970914663610813,"score_spread":0.1339834147069988,"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."}}