{"id":"W4223433135","doi":"10.1007/s10661-022-09942-5","title":"Successful application of wastewater-based epidemiology in prediction and monitoring of the second wave of COVID-19 with fragmented sewerage systems–a case study of Jaipur (India)","year":2022,"lang":"en","type":"article","venue":"Environmental Monitoring and Assessment","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Australian Research Council; Canadian Institutes of Health Research","keywords":"Effluent; Wastewater; Sewage treatment; Chlorine; Sewerage; Coronavirus disease 2019 (COVID-19); Moving bed biofilm reactor; Environmental science; Veterinary medicine; Biology; Medicine; Environmental engineering; Chemistry; Biofilm; Bacteria; Internal medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006432701,0.0005500123,0.0004379959,0.001339969,0.0008857918,0.001388302,0.0008448662,0.0009426402,0.0006201873],"category_scores_gemma":[0.001001026,0.0003021306,0.0005796092,0.001428646,0.0006141971,0.0004613984,0.0008182267,0.0003659902,0.0001907079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001046202,"about_ca_system_score_gemma":0.001487701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05222134,"about_ca_topic_score_gemma":0.06674305,"domain_scores_codex":[0.9992716,0.0002241805,0.00004553208,0.0001439275,0.000175944,0.0001388684],"domain_scores_gemma":[0.9993157,0.0002540216,0.00009756918,0.00006596536,0.0002065358,0.00006018594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003045808,0.0007047841,0.8928875,0.0001995002,0.0001349026,0.007869001,0.003069281,0.01473044,0.02663667,0.000441467,0.0003387953,0.05268308],"study_design_scores_gemma":[0.00003470898,0.002585034,0.8510318,0.00007191223,0.0003817191,0.005886801,0.01723826,0.08001316,0.03753674,0.0008911742,0.004211651,0.0001170437],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950295,0.00007537834,0.002969752,0.00008999986,0.000007186738,0.00006127122,0.0001480222,0.0000447729,0.001574221],"genre_scores_gemma":[0.9964942,0.00007606432,0.002758959,0.000014018,0.000002408095,0.00001095915,0.00008169474,0.000005497484,0.00055613],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05222134,"threshold_uncertainty_score":0.1038347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03721336151970302,"score_gpt":0.3137078029969531,"score_spread":0.2764944414772501,"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."}}