{"id":"W2757549792","doi":"10.1016/j.chroma.2017.09.055","title":"Determination of the bioavailability of selected pharmaceutical residues in fish plasma using liquid chromatography coupled to tandem mass spectrometry","year":2017,"lang":"en","type":"article","venue":"Journal of Chromatography A","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Chemistry; Chromatography; Solid phase extraction; Sample preparation; Effluent; Liquid chromatography–mass spectrometry; Mass spectrometry; Metabolite; Extraction (chemistry); Tandem mass spectrometry; Electrospray; Contamination","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":[0.0003188435,0.0004130126,0.0002684465,0.0004623186,0.0003827297,0.0003567577,0.0002204749,0.0005681149,0.0008158525],"category_scores_gemma":[0.0005426862,0.0002235726,0.0003008411,0.0002358161,0.0004059902,0.0002627559,0.0002707885,0.0004423952,0.0004015237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005579981,"about_ca_system_score_gemma":0.0009345685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005950824,"about_ca_topic_score_gemma":0.00771447,"domain_scores_codex":[0.9997014,0.00003720806,0.00001245425,0.00009439191,0.000123337,0.00003104151],"domain_scores_gemma":[0.9998247,0.00004781471,0.00004048175,0.00001021977,0.00005527097,0.00002144322],"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":[0.0003975039,0.00003263849,0.005805352,0.00003707993,0.00004423385,0.00004681142,0.00003404581,0.0001627318,0.9884627,0.00004399233,0.00008409093,0.004848816],"study_design_scores_gemma":[0.00004399938,0.0006545128,0.03416808,0.00001290222,0.00007486902,0.0005150285,0.00007734778,0.004209793,0.9586129,0.0001162583,0.001489384,0.00002497935],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.980495,0.001369924,0.01536172,0.0001838829,0.00003601333,0.00006571992,0.0006976617,0.0001492133,0.001640944],"genre_scores_gemma":[0.9763201,0.001384438,0.01704896,0.0002823559,0.00003095189,0.00009809697,0.0005249363,0.00003130545,0.004278777],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005950824,"threshold_uncertainty_score":0.01183242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02655193080501987,"score_gpt":0.3061089695184924,"score_spread":0.2795570387134725,"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."}}