{"id":"W2964848187","doi":"10.1039/c9an01195a","title":"A microscale solid-phase microextraction probe for the <i>in situ</i> analysis of perfluoroalkyl substances and lipids in biological tissues using mass spectrometry","year":2019,"lang":"en","type":"article","venue":"The Analyst","topic":"Per- and polyfluoroalkyl substances research","field":"Environmental Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"IONICS Mass Spectrometry (Canada)","funders":"Fundamental Research Funds for the Central Universities; Guangdong Academy of Sciences; Sun Yat-sen University; Natural Science Foundation of Guangdong Province; National Natural Science Foundation of China","keywords":"Microscale chemistry; In situ; Mass spectrometry; Solid-phase microextraction; Chemistry; Chromatography; Lipidomics; Gas chromatography–mass spectrometry; Analytical Chemistry (journal); Environmental chemistry; Organic chemistry; Biochemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001057717,0.000130588,0.0003483783,0.0001821255,0.0001202938,0.0000405648,0.0003287701,0.00006782374,0.0003635858],"category_scores_gemma":[0.00002303176,0.00007380141,0.0001270933,0.001655744,0.0003093058,0.0001432503,0.0000695543,0.0001952922,0.00001143605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001147131,"about_ca_system_score_gemma":0.00000991611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001201967,"about_ca_topic_score_gemma":0.005332743,"domain_scores_codex":[0.9986587,0.0001646274,0.000304608,0.0003161654,0.0002166019,0.0003392605],"domain_scores_gemma":[0.9991722,0.0003625169,0.000112617,0.0003027273,0.00001021935,0.00003978796],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001164546,0.0000740088,0.2850751,0.000006896269,0.00007595781,0.000001105731,0.000469065,0.0007164574,0.7092556,0.00001251367,0.00001400269,0.004182816],"study_design_scores_gemma":[0.002247269,0.0004702694,0.6232365,0.00005171469,0.0006644737,0.000009565974,0.004836638,0.1000609,0.2617063,0.0004966182,0.005702902,0.0005168426],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9866026,0.01054528,0.001934271,0.0001774439,0.00003033841,0.000399967,0.00002364929,0.000005422639,0.0002810502],"genre_scores_gemma":[0.9979103,0.001044715,0.0007449586,0.00003911096,0.00002520705,0.00001742064,0.000009663463,0.000006615875,0.0002020344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4475494,"threshold_uncertainty_score":0.3981009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03023601074315745,"score_gpt":0.3484965138420527,"score_spread":0.3182605030988953,"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."}}