{"id":"W2065192535","doi":"10.1016/j.scitotenv.2013.02.074","title":"A multi-assay screening approach for assessment of endocrine-active contaminants in wastewater effluent samples","year":2013,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":42,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Genomics; Carleton University; Environment and Climate Change Canada; Agriculture and Agri-Food Canada; University of Ottawa; Ministry of the Environment, Conservation and Parks; Trent University","funders":"Agriculture and Agri-Food Canada; Trent University","keywords":"Bioassay; Chemistry; Wastewater; Environmental chemistry; Endocrine disruptor; Polybrominated diphenyl ethers; Chromatography; Effluent; Metabolite; Contamination; Liquid chromatography–mass spectrometry; Thyroid hormone receptor; In vitro toxicology; In vitro; Biochemistry; Mass spectrometry; Hormone; Biology; Pollutant; Endocrine system; Environmental engineering; Environmental science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00167391,0.001291789,0.001272878,0.002941508,0.0007342936,0.0009425226,0.001100143,0.001497999,0.0007687056],"category_scores_gemma":[0.001134718,0.001032699,0.001201964,0.001021488,0.000472437,0.0005102186,0.001530734,0.001296621,0.0007863587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00056959,"about_ca_system_score_gemma":0.0008040239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001795146,"about_ca_topic_score_gemma":0.00612118,"domain_scores_codex":[0.9971794,0.0004980529,0.0001832373,0.0006194553,0.001352232,0.0001677509],"domain_scores_gemma":[0.999105,0.0002419943,0.000101111,0.0001427821,0.000335834,0.00007319303],"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":[0.0001055297,0.0001282947,0.001358701,0.0000684496,0.00005556244,0.00003276131,0.00002845765,0.0004814528,0.9809614,0.00005835685,0.00006672193,0.01665434],"study_design_scores_gemma":[0.00002380236,0.001066242,0.01114977,0.00001300026,0.0001829567,0.0008852176,0.00006395912,0.01637015,0.9673267,0.0001440864,0.002677767,0.00009642263],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4801971,0.003926866,0.5081229,0.0002813333,0.0001930233,0.001195475,0.001298886,0.001592231,0.00319214],"genre_scores_gemma":[0.5343436,0.002017618,0.4517118,0.0004216155,0.00004903458,0.001115561,0.001159517,0.00006203455,0.009119266],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002941508,"threshold_uncertainty_score":0.008852601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04917845088062975,"score_gpt":0.2992486377436487,"score_spread":0.250070186863019,"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."}}