{"id":"W2509736886","doi":"10.1080/23311843.2016.1222690","title":"Modeling the loading and fate of estrogens in wastewater treatment plants","year":2016,"lang":"en","type":"article","venue":"Sustainable Environment","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Estrogen; Endocrine system; Estrone; Vitellogenin; Effluent; Wastewater; Population; Environmental science; Sewage treatment; Environmental chemistry; Biology; Chemistry; Hormone; Environmental engineering; Endocrinology; Medicine; Environmental health","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001954223,0.000170421,0.0001582731,0.00002658884,0.00008660263,0.0000102868,0.000121968,0.000041181,0.0006418123],"category_scores_gemma":[0.000008114276,0.00008525549,0.00003902996,0.00004089183,0.0003004132,0.0001718045,0.0002873944,0.00005050224,0.000103281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004988484,"about_ca_system_score_gemma":0.000004042076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003355499,"about_ca_topic_score_gemma":0.000008056895,"domain_scores_codex":[0.9987321,0.00005342566,0.0002220625,0.000285348,0.0002014132,0.0005056349],"domain_scores_gemma":[0.9995751,0.0000455458,0.00003904745,0.0002169427,4.800636e-7,0.0001228383],"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":[0.0002382586,0.001018394,0.3211005,0.00006306347,0.00008847113,0.0002951615,0.002619667,0.07501636,0.5554899,0.0006940123,0.00006159484,0.04331457],"study_design_scores_gemma":[0.007799386,0.001336897,0.1212944,0.0002357559,0.0001510585,0.0001065547,0.01032152,0.04457624,0.7818877,0.008136737,0.02270155,0.001452218],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976744,0.000140261,0.0001843126,0.0008127995,0.00001351354,0.0002902607,0.000005791469,0.000007114887,0.0008715247],"genre_scores_gemma":[0.9969885,0.0008755859,0.0001092332,0.00005399785,0.000009575052,0.00001154049,9.460119e-7,0.00001318481,0.001937437],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2263978,"threshold_uncertainty_score":0.7027395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01775403951304356,"score_gpt":0.2401619127215978,"score_spread":0.2224078732085542,"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."}}