{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009831187,0.0007083299,0.0004648332,0.001834133,0.003581099,0.001951677,0.0008154883,0.000982995,0.001077004],"category_scores_gemma":[0.001045928,0.0002314939,0.0006297247,0.002453983,0.0005902256,0.0003307507,0.000619774,0.0004425459,0.0001913514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02510522,"about_ca_system_score_gemma":0.03149975,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9595457,"about_ca_topic_score_gemma":0.9796515,"domain_scores_codex":[0.9979318,0.0001237735,0.00006071452,0.0001519782,0.001476747,0.0002548918],"domain_scores_gemma":[0.9989964,0.00003443593,0.00004256189,0.00001187741,0.000847195,0.00006759443],"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":[0.003182678,0.0007402158,0.3370243,0.001400239,0.0003752763,0.001022681,0.002026058,0.0220469,0.4007925,0.002454834,0.005842812,0.2230915],"study_design_scores_gemma":[0.0001859352,0.002413565,0.5881054,0.0001816523,0.0005893409,0.0005317892,0.006239803,0.01416347,0.3135001,0.0009672385,0.07293728,0.0001844657],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9828253,0.001512306,0.001357615,0.0003709462,0.00003493343,0.0001430231,0.001187161,0.00002942995,0.0125392],"genre_scores_gemma":[0.9825585,0.002743077,0.002888564,0.0002398886,0.00001152011,0.00003319933,0.0007575957,0.00001064644,0.01075714],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04045427,"threshold_uncertainty_score":0.182152,"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."}}