{"id":"W4403936291","doi":"10.1214/24-aoas1915","title":"Multisite disease analytics with applications to estimating COVID-19 undetected cases in Canada","year":2024,"lang":"en","type":"article","venue":"The Annals of Applied Statistics","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; Simon Fraser University","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Analytics; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Data science; Pandemic; Computer science; Disease; Medicine; Infectious disease (medical specialty); Virology; Outbreak","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002086934,0.0007494243,0.0006696937,0.001783867,0.0007872851,0.001289663,0.001523491,0.0006209914,0.001663339],"category_scores_gemma":[0.009269441,0.0003749938,0.0007664852,0.002485633,0.000688405,0.0006061988,0.001421868,0.001112351,0.0001770955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009583004,"about_ca_system_score_gemma":0.01100207,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9408332,"about_ca_topic_score_gemma":0.9142351,"domain_scores_codex":[0.9992694,0.0002123133,0.00003872107,0.000204435,0.0001642031,0.0001109912],"domain_scores_gemma":[0.9965101,0.001833889,0.0004348734,0.000272902,0.0007678978,0.0001803684],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001235778,0.00007515797,0.1272946,0.00009241829,0.0001684054,0.0002036698,0.0003528596,0.8146465,0.0005862485,0.01021273,0.004216517,0.04202729],"study_design_scores_gemma":[0.0000114864,0.00001006233,0.01383206,0.00001647159,0.00001418256,0.00002658363,0.0001242779,0.9798605,0.0001657764,0.004711749,0.001207069,0.00001981464],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6556212,0.001424578,0.3118364,0.004609494,0.0000918883,0.0003125094,0.0177635,0.002481639,0.005858771],"genre_scores_gemma":[0.9476632,0.0004266178,0.04593604,0.0001206755,0.00002858213,0.00006951796,0.003837999,0.00007429133,0.001843032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05916679,"threshold_uncertainty_score":0.1190304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3456598966050817,"score_gpt":0.4734745204622825,"score_spread":0.1278146238572008,"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."}}