{"id":"W4382542806","doi":"10.1016/j.trac.2023.117167","title":"Direct solid-phase microextraction-mass spectrometry facilitates rapid analysis and green analytical chemistry","year":2023,"lang":"en","type":"article","venue":"TrAC Trends in Analytical Chemistry","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":63,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"National Institute of Mental Health; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Solid-phase microextraction; Sample preparation; Mass spectrometry; Chromatography; Chemistry; Analyte; Gas chromatography–mass spectrometry; Analytical technique; Analytical Chemistry (journal); Process engineering; Organic chemistry","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":[0.0007193366,0.001068638,0.0006700915,0.0009225255,0.0005434129,0.00141974,0.001008204,0.001158683,0.004683751],"category_scores_gemma":[0.001167453,0.0006445337,0.0004021755,0.0006231406,0.0006551866,0.001452397,0.001131532,0.001933906,0.006255551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005570262,"about_ca_system_score_gemma":0.001111854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007374866,"about_ca_topic_score_gemma":0.004324119,"domain_scores_codex":[0.9986054,0.000129636,0.00004284311,0.0003487649,0.0007921816,0.0000811139],"domain_scores_gemma":[0.9992247,0.0003220366,0.00009417583,0.00009493183,0.0002132638,0.00005086824],"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":[0.00004955822,0.00005681624,0.0002613933,0.0001075133,0.00001098946,0.000036065,0.00001351214,0.0000589682,0.9763952,0.0006355763,0.00137688,0.02099747],"study_design_scores_gemma":[0.00001372276,0.00009207903,0.001094701,0.00001490274,0.00001500094,0.000217728,0.00001994171,0.001526596,0.9820495,0.0006687086,0.01427398,0.00001318535],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2179531,0.0204048,0.682286,0.004674485,0.002809653,0.001242056,0.007992635,0.01068922,0.05194809],"genre_scores_gemma":[0.4015458,0.01515674,0.5149423,0.003184732,0.0008957815,0.0004934496,0.005368455,0.0008283365,0.05758438],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004683751,"threshold_uncertainty_score":0.01566875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03284813236295149,"score_gpt":0.3610462522325018,"score_spread":0.3281981198695503,"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."}}