{"id":"W2086956259","doi":"10.1016/j.watres.2014.11.008","title":"Distribution of selected antiandrogens and pharmaceuticals in a highly impacted watershed","year":2014,"lang":"en","type":"article","venue":"Water Research","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":83,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Water Network; U.S. Environmental Protection Agency","keywords":"Triclosan; Triclocarban; Environmental impact of pharmaceuticals and personal care products; Effluent; Environmental science; Surface water; Outfall; Environmental chemistry; Endocrine disruptor; Vitellogenin; Sewage treatment; Hydrology (agriculture); Chemistry; Environmental engineering; Biology; Endocrine system; Fishery; Medicine; Fish <Actinopterygii>; Geology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001049944,0.0001031623,0.0001585179,0.00005334117,0.00007285138,0.00002427203,0.0001405438,0.00006296542,0.0006952902],"category_scores_gemma":[0.00008224202,0.00006694534,0.00002104596,0.0003284786,0.0005384618,0.0001423885,0.0003027669,0.0002497527,0.0002714633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009240708,"about_ca_system_score_gemma":0.000003442184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002908996,"about_ca_topic_score_gemma":0.000015179,"domain_scores_codex":[0.9981638,0.0003076187,0.0002052522,0.0002625725,0.0004131333,0.0006476793],"domain_scores_gemma":[0.9995561,0.00003855861,0.0000139711,0.0001350863,0.000009698659,0.0002466237],"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":[0.00006121585,0.0001444212,0.1336437,0.00002013879,0.000005780302,0.000006897497,0.0001875545,0.00001806981,0.8637963,0.00002317944,0.0001730965,0.001919608],"study_design_scores_gemma":[0.0006101767,0.0001045302,0.2672524,0.00001381137,0.000004595815,0.000007308355,0.00001353178,0.002098293,0.7270102,0.0002826258,0.002516495,0.00008598752],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979472,0.00001510455,0.00004361335,0.0008682005,0.00001255544,0.0001979235,0.00001135202,0.00001375049,0.0008903121],"genre_scores_gemma":[0.9996423,0.00005253003,0.00004029471,0.00005010573,0.00001173404,0.000002845012,0.00004376081,0.000009295232,0.0001471775],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1367861,"threshold_uncertainty_score":0.7612939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0530377709207682,"score_gpt":0.3582033999371427,"score_spread":0.3051656290163745,"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."}}