{"id":"W2068552774","doi":"10.1016/j.chroma.2006.03.017","title":"Simultaneous determination of endocrine-disrupting phenols and steroid estrogens in sediment by gas chromatography–mass spectrometry","year":2006,"lang":"en","type":"article","venue":"Journal of Chromatography A","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":121,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"National Key Research and Development Program of China","keywords":"Chemistry; Chromatography; Derivatization; Nonylphenol; Mass spectrometry; Gas chromatography; Bisphenol A; Gas chromatography–mass spectrometry; Selected ion monitoring; Fractionation; Sediment; Steroid; Environmental chemistry; Endocrine disruptor; Endocrine system; Hormone; Organic chemistry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001960903,0.0004136411,0.000260835,0.0007007449,0.0004140936,0.0003530693,0.000205612,0.0004075724,0.0003601784],"category_scores_gemma":[0.0003247788,0.0002713225,0.0001443944,0.000571603,0.0003087152,0.0002449053,0.0002313425,0.0003048908,0.0002069717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004111998,"about_ca_system_score_gemma":0.0005816371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007241884,"about_ca_topic_score_gemma":0.01099481,"domain_scores_codex":[0.999785,0.00002373538,0.00001004549,0.00005195028,0.0001003236,0.00002898136],"domain_scores_gemma":[0.9998251,0.0000396243,0.00003348655,0.00000894529,0.00007022722,0.00002275322],"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":[0.0001724757,0.00002973953,0.00900794,0.00002515675,0.0000231231,0.00005578693,0.00003656881,0.0002654741,0.9848056,0.00005031118,0.00006538357,0.005462482],"study_design_scores_gemma":[0.00002552557,0.000249787,0.04213315,0.000008698631,0.00004626918,0.0002557969,0.0001059437,0.004272044,0.9506506,0.0001552596,0.00208039,0.00001663328],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9832138,0.001231556,0.01340742,0.0001162857,0.00003450134,0.00002856017,0.0006151872,0.0001510199,0.001201758],"genre_scores_gemma":[0.9859529,0.0009009969,0.01037405,0.00009604009,0.00002102611,0.00002371383,0.00046126,0.00001818279,0.002151981],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007241884,"threshold_uncertainty_score":0.01439947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006122577891749964,"score_gpt":0.2441996024127981,"score_spread":0.2380770245210481,"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."}}