{"id":"W2028135657","doi":"10.1016/j.scitotenv.2006.11.018","title":"An assessment of estrogenic organic contaminants in Canadian wastewaters","year":2006,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":258,"is_retracted":false,"has_abstract":false,"ca_institutions":"Fisheries and Oceans Canada; University of Alberta","funders":"Division of Ocean Sciences; Natural Resources Canada; Fisheries and Oceans Canada; University of Victoria","keywords":"Effluent; Chemistry; Wastewater; Nonylphenol; Environmental chemistry; Chromatography; Stigmasterol; Environmental engineering; Environmental science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008328634,0.0001444793,0.000154869,0.00004320779,0.0001893062,0.00001493373,0.0009510521,0.00003268431,0.0009721848],"category_scores_gemma":[0.000009753513,0.00008270286,0.00006092209,0.0003303172,0.002617504,0.0002424225,0.0003672216,0.0001330049,0.00005526622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007223797,"about_ca_system_score_gemma":0.00006845474,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06098548,"about_ca_topic_score_gemma":0.003494739,"domain_scores_codex":[0.9980612,0.00008294143,0.0003062614,0.000288348,0.0006904872,0.0005707665],"domain_scores_gemma":[0.9990936,0.00002065346,0.0001286022,0.0005465672,0.00000134876,0.0002092648],"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":[0.000003665053,0.0001967904,0.04160364,0.000002751365,0.000002774618,0.000001833515,0.00008720496,0.05877772,0.898852,0.0001464336,0.000008865579,0.0003163255],"study_design_scores_gemma":[0.000187543,0.00007057204,0.7241803,0.00001129126,0.00001294864,0.000009203838,0.00008559939,0.006183927,0.2689306,0.0002142315,0.00002082859,0.00009284744],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962848,0.00001487216,0.000007740097,0.0004800959,0.00007748618,0.000278748,0.00001114367,0.000003311263,0.00284181],"genre_scores_gemma":[0.9994621,0.00001059237,0.0002044594,0.00003474425,0.000008521524,0.000002552633,0.000001014414,0.000008675617,0.0002673435],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6825767,"threshold_uncertainty_score":0.9999411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009550335276430804,"score_gpt":0.2615776658499585,"score_spread":0.2520273305735277,"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."}}