{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004177604,0.0008833593,0.0005974304,0.0004273497,0.0003504476,0.0003713531,0.0004817712,0.0005301764,0.0004593162],"category_scores_gemma":[0.0004661706,0.0004597527,0.0005140768,0.0003189785,0.0003223646,0.0003095439,0.000539647,0.0005928713,0.0003527517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004997696,"about_ca_system_score_gemma":0.0006936901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001271179,"about_ca_topic_score_gemma":0.004174038,"domain_scores_codex":[0.9993235,0.00005658569,0.00003554135,0.0002279458,0.0003206868,0.00003576017],"domain_scores_gemma":[0.9998313,0.00004711441,0.00002926388,0.00002087581,0.00005515218,0.00001614808],"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":[0.00001842141,0.00001118841,0.0002492175,0.0000523132,0.000009951373,0.00002830144,0.00001131141,0.00009648859,0.995643,0.00002985732,0.00002315044,0.003826805],"study_design_scores_gemma":[0.000006534648,0.0001890752,0.003128292,0.000004500708,0.00002539019,0.0003083419,0.00001197825,0.002344741,0.9920521,0.00004233037,0.001871658,0.00001507029],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7438111,0.005144235,0.2453349,0.0002695741,0.000208753,0.0004786089,0.001107513,0.00089704,0.002748278],"genre_scores_gemma":[0.6351404,0.003803976,0.3557823,0.0001917449,0.00004558734,0.0002672084,0.0008220655,0.0000904992,0.003856165],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.001271179,"threshold_uncertainty_score":0.003626108,"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."}}