{"id":"W2992796619","doi":"10.2175/193864716819714159","title":"MONITORING CHEMICAL SUBSTANCES IN CANADIAN MUNICIPAL WASTEWATER","year":2016,"lang":"en","type":"article","venue":"Proceedings of the Water Environment Federation","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Wastewater; Environmental science; Waste management; Environmental chemistry; Water resource management; Environmental engineering; Environmental planning; Chemistry; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.000886548,0.000525695,0.0005140028,0.002915385,0.004934193,0.002265282,0.001019423,0.001144865,0.001029237],"category_scores_gemma":[0.001190421,0.000310612,0.0004966321,0.003533609,0.0008846304,0.000407035,0.0007081507,0.0006231706,0.0002443376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02932935,"about_ca_system_score_gemma":0.0391886,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9864109,"about_ca_topic_score_gemma":0.9922017,"domain_scores_codex":[0.9978458,0.00008529525,0.00008835086,0.0002391072,0.001436419,0.000305013],"domain_scores_gemma":[0.9989455,0.0000502804,0.00006143592,0.00001636801,0.0008504479,0.00007584703],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001137721,0.0005161601,0.5298923,0.0007779928,0.0002578547,0.0006178891,0.002530421,0.008479331,0.2872084,0.001160269,0.007742402,0.1596792],"study_design_scores_gemma":[0.00008910495,0.0003219582,0.8117604,0.0001029409,0.0002295455,0.000279554,0.003543597,0.008769303,0.1336902,0.0002960485,0.04079393,0.0001234242],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.985352,0.0008685762,0.0009715534,0.0003583114,0.00003862728,0.0001325736,0.001850588,0.00006939828,0.01035836],"genre_scores_gemma":[0.9856433,0.001324875,0.003337599,0.000219075,0.00001115176,0.00004349522,0.001399413,0.00002032748,0.008000759],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02932935,"threshold_uncertainty_score":0.2128003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01604929919308042,"score_gpt":0.2259770362619833,"score_spread":0.2099277370689029,"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."}}