{"id":"W2151099907","doi":"10.1039/c0em00550a","title":"High throughput analysis of solid-bound endocrine disruptors by LDTD-APCI-MS/MS","year":2011,"lang":"en","type":"article","venue":"Journal of Environmental Monitoring","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Université de Montréal; Natural Sciences and Engineering Research Council","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chemistry; Chromatography; Atmospheric-pressure chemical ionization; Extraction (chemistry); Detection limit; Solid phase extraction; Matrix (chemical analysis); Mass spectrometry; Environmental chemistry; Triclocarban; Dibenzofuran; Sample preparation; Chemical ionization; Ionization; Triclosan","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":[0.0009194213,0.0009901484,0.0008550024,0.001195866,0.0006480724,0.0006536308,0.0006573382,0.000551743,0.001575529],"category_scores_gemma":[0.001026489,0.0003841082,0.0002331327,0.0007320693,0.0005143547,0.0004381753,0.0005076709,0.0006528315,0.001285189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001071828,"about_ca_system_score_gemma":0.001309812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007878004,"about_ca_topic_score_gemma":0.02346483,"domain_scores_codex":[0.9989503,0.0001023285,0.00003792646,0.0001880427,0.0006591027,0.00006237342],"domain_scores_gemma":[0.99936,0.0002007491,0.00006894757,0.00003905064,0.0002860099,0.00004518278],"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":[0.0000721199,0.00004928931,0.0007618182,0.00008036369,0.00002458855,0.00004594697,0.00001970265,0.0002855356,0.9880852,0.00003465099,0.0001528507,0.01038792],"study_design_scores_gemma":[0.00004249413,0.0003722964,0.008177733,0.00001115936,0.00005487163,0.0004655565,0.0000383748,0.01189618,0.9741042,0.00009623238,0.004694834,0.00004600859],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6256743,0.003518465,0.3540288,0.0004325212,0.00008067436,0.001098442,0.005681182,0.005098191,0.004387463],"genre_scores_gemma":[0.5860328,0.004096985,0.3902885,0.0005100587,0.00006896821,0.001443424,0.005248766,0.0003007132,0.01200979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007878004,"threshold_uncertainty_score":0.01566428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0282349908846264,"score_gpt":0.2929875019541479,"score_spread":0.2647525110695215,"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."}}