{"id":"W192159030","doi":"10.2166/wqrj.2007.018","title":"Polycyclic and Nitro Musks in Canadian Municipal Wastewater: Occurrence and Removal in Wastewater Treatment","year":2007,"lang":"en","type":"article","venue":"Water Quality Research Journal","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of the Environment, Conservation and Parks; Toronto Public Health; Ministry of Environment; University of Guelph; Environment and Climate Change Canada","funders":"","keywords":"Effluent; Wastewater; Chemistry; Environmental chemistry; Activated sludge; Sewage treatment; Secondary treatment; Nitro; Environmental science; Environmental engineering; Organic chemistry","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":[0.000211227,0.0004818823,0.0003703003,0.0008907528,0.001377205,0.0007398419,0.0004001479,0.0004081318,0.0006072888],"category_scores_gemma":[0.0003282536,0.0001912505,0.000288453,0.001224448,0.0003647926,0.0001567024,0.0002381152,0.0002587208,0.0001770682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006801847,"about_ca_system_score_gemma":0.005916078,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8070309,"about_ca_topic_score_gemma":0.9037018,"domain_scores_codex":[0.9992172,0.00002360131,0.00002413886,0.00008698153,0.0005093859,0.0001386982],"domain_scores_gemma":[0.9996963,0.00001261431,0.00003298006,0.000004688089,0.0002133043,0.0000400887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0005572999,0.00009406715,0.07985707,0.0003832584,0.00004689833,0.0001556883,0.0005001039,0.001718712,0.8935016,0.00007001185,0.0002901202,0.0228252],"study_design_scores_gemma":[0.00002264032,0.0006227182,0.6071835,0.00003725592,0.00008136781,0.0002760856,0.001159943,0.003321428,0.381103,0.00005105668,0.006089041,0.00005205326],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986192,0.0002656435,0.0002559834,0.00001823829,0.000002628159,0.00001811154,0.000275625,0.00001514887,0.000529437],"genre_scores_gemma":[0.9951982,0.0004610268,0.001368919,0.00002546253,0.000002030868,0.00001403033,0.0007198675,0.000009043049,0.002201428],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1929691,"threshold_uncertainty_score":0.3882111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1279985394884222,"score_gpt":0.4135384732793684,"score_spread":0.2855399337909462,"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."}}