{"id":"W4378904450","doi":"10.14745/ccdr.v49i05a01","title":"Coupling wastewater-based epidemiological surveillance and modelling of SARS-COV-2/COVID-19: Practical applications at the Public Health Agency of Canada","year":2023,"lang":"en","type":"article","venue":"Canada Communicable Disease Report","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada; Public Health Agency of Canada","funders":"","keywords":"Public health; Agency (philosophy); Coronavirus disease 2019 (COVID-19); Environmental health; Medicine; Infectious disease (medical specialty); Business; Disease; Environmental planning; Environmental science; Sociology; Pathology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001117907,0.0009486037,0.0007355224,0.0007038433,0.001264215,0.002059933,0.001625585,0.001975033,0.002583972],"category_scores_gemma":[0.003788784,0.0005235029,0.001089037,0.0009419557,0.001133919,0.0006400634,0.001354871,0.001217769,0.0002137403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01362014,"about_ca_system_score_gemma":0.01564501,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9563059,"about_ca_topic_score_gemma":0.8838718,"domain_scores_codex":[0.999388,0.0001526334,0.0000290557,0.0001090603,0.0001184675,0.0002028519],"domain_scores_gemma":[0.9983399,0.0006635002,0.0001285907,0.0000441259,0.0006899997,0.0001338594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00001691604,0.00001571935,0.004333212,0.00002233237,0.00001198745,0.00004278054,0.00004034016,0.9904266,0.000159718,0.002785074,0.0005887065,0.001556688],"study_design_scores_gemma":[0.000006714186,0.000008591203,0.001211652,0.00000622984,0.000007679652,0.000005093159,0.00008964483,0.9972253,0.00005750925,0.0007910005,0.0005798303,0.00001082613],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7035533,0.002021631,0.2198038,0.008124783,0.0002798517,0.000514659,0.008648126,0.0007425867,0.0563113],"genre_scores_gemma":[0.9721111,0.0006379593,0.01623767,0.0001824854,0.00003839802,0.000132714,0.001131014,0.0000488732,0.009479774],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04369414,"threshold_uncertainty_score":0.09882152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2327454730672307,"score_gpt":0.3842486184062504,"score_spread":0.1515031453390196,"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."}}