{"id":"W2327370663","doi":"10.1021/jf506212j","title":"Direct Immersion Solid-Phase Microextraction with Matrix-Compatible Fiber Coating for Multiresidue Pesticide Analysis of Grapes by Gas Chromatography–Time-of-Flight Mass Spectrometry (DI-SPME-GC-ToFMS)","year":2015,"lang":"en","type":"article","venue":"Journal of Agricultural and Food Chemistry","topic":"Pesticide Residue Analysis and Safety","field":"Agricultural and Biological Sciences","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Sigma-Aldrich Corporation; Agilent Foundation","keywords":"Solid-phase microextraction; Chromatography; Mass spectrometry; Chemistry; Gas chromatography–mass spectrometry; Gas chromatography","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":[],"consensus_categories":[],"category_scores_codex":[0.0002952921,0.0002410247,0.0008079128,0.00006209635,0.0001199479,0.00004838875,0.000194399,0.0001262012,0.00008114042],"category_scores_gemma":[0.0000562638,0.0000869884,0.000477675,0.001054417,0.00008072786,0.0001993002,0.00002584705,0.0001484923,4.727325e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003281161,"about_ca_system_score_gemma":0.00001724555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007224234,"about_ca_topic_score_gemma":0.00002248176,"domain_scores_codex":[0.9983458,0.0000445058,0.00072053,0.0002351726,0.0004002798,0.0002537485],"domain_scores_gemma":[0.9977565,0.0002821986,0.001168871,0.0000567219,0.0005107468,0.0002249244],"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":[0.0002116665,0.000240159,0.00851236,0.00005136954,0.001109596,0.000002412684,0.00005096574,0.0003319152,0.9881818,8.675343e-7,0.0006278753,0.000678985],"study_design_scores_gemma":[0.0009062213,0.00132598,0.06227298,0.0001244537,0.002061201,0.00008052552,0.001289028,0.0002915936,0.9312804,0.00001463694,0.00009702346,0.0002559285],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972506,0.002095125,0.00007084455,0.0001921143,0.00001520036,0.0000946724,0.0001335036,0.000009491499,0.0001384158],"genre_scores_gemma":[0.9986081,0.0001737295,0.0007967743,0.000006432414,0.0001263942,0.000002683429,0.0001717785,0.000001960705,0.0001121067],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0569014,"threshold_uncertainty_score":0.3547284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01160046202002221,"score_gpt":0.2531121338798018,"score_spread":0.2415116718597796,"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."}}