{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001086943,0.001085185,0.00191827,0.000683973,0.0002120052,0.0001984175,0.0008322313,0.0009697716,0.02373581],"category_scores_gemma":[0.001073171,0.00113303,0.0009810928,0.007223787,0.0008358121,0.0002234027,0.0003116155,0.001654416,0.0001285945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006773379,"about_ca_system_score_gemma":0.0001525612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007454462,"about_ca_topic_score_gemma":0.000009861265,"domain_scores_codex":[0.9930338,0.00007400662,0.00177557,0.002210791,0.001138951,0.001766844],"domain_scores_gemma":[0.9956577,0.001359393,0.0003105575,0.001317073,0.0001608283,0.001194447],"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":[0.000420725,0.001460708,0.02132794,0.001696056,0.005072967,0.001552636,0.0002342885,0.0002192124,0.9479265,0.0000328465,0.001870388,0.01818571],"study_design_scores_gemma":[0.004163092,0.0000490815,0.009453973,0.0001698257,0.003649502,0.0001204564,0.001067783,0.1187573,0.8531066,0.0006820878,0.006029279,0.00275101],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7553958,0.0005170438,0.003307908,0.001785419,0.00005849159,0.0001019948,0.0006886964,0.00110118,0.2370434],"genre_scores_gemma":[0.9252583,0.0002583741,0.002752709,0.00005681022,0.000359078,0.00005495546,0.001193984,0.000116272,0.06994952],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1698625,"threshold_uncertainty_score":0.999112,"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."}}