{"id":"W3183462631","doi":"10.1002/wer.1615","title":"Digital solutions for continued operation of WRRFs during pandemics and other interruptions","year":2021,"lang":"en","type":"article","venue":"Water Environment Research","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Instrumentation (computer programming); Preparedness; Pandemic; Scheduling (production processes); Risk analysis (engineering); Operations management; Engineering; Computer science; Coronavirus disease 2019 (COVID-19); Business","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002860732,0.00005251278,0.00009745789,0.00007578983,0.0001513476,0.00003457022,0.00002507534,0.00004306058,0.00005943614],"category_scores_gemma":[0.00009684889,0.00004105448,0.00003537598,0.00003714797,0.0001108283,0.00006727643,0.0001067898,0.0001259536,0.00002460065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005706849,"about_ca_system_score_gemma":0.00001365926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008658646,"about_ca_topic_score_gemma":0.000006404527,"domain_scores_codex":[0.999244,0.00003187367,0.0001507472,0.0001676925,0.0001747329,0.0002309299],"domain_scores_gemma":[0.9997237,0.00005559951,0.00001267342,0.000136511,0.00003856191,0.00003297074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003971783,0.00008390236,0.01209096,0.00004082137,0.00002514156,0.000003540323,0.0003664918,0.000007192796,0.985294,0.00004110957,0.00001521192,0.001991889],"study_design_scores_gemma":[0.001082836,0.0001145371,0.005025774,0.00004450764,0.00001353672,0.00005403479,0.0003944192,0.001167778,0.9788444,0.00008584842,0.01311821,0.00005409794],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963741,0.0000595723,0.001764236,0.0003573793,0.00001991555,0.0002597141,0.00001128635,0.00001393598,0.001139864],"genre_scores_gemma":[0.9968399,0.00001448887,0.0003655292,0.00004916614,0.0000535617,0.00004962898,0.00001882467,0.00001269263,0.002596171],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.013103,"threshold_uncertainty_score":0.1674153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1429173307098592,"score_gpt":0.3646479900196636,"score_spread":0.2217306593098044,"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."}}