{"id":"W6903236640","doi":"10.1021/jf903849n.s001","title":"Development and Interlaboratory Validation of a QuEChERS-Based Liquid Chromatography−Tandem Mass Spectrometry Method for Multiresidue Pesticide Analysis","year":2016,"lang":"en","type":"article","venue":"Figshare","topic":"Pesticide Residue Analysis and Safety","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quechers; Pesticide residue; Pesticide; Sample preparation; Mass spectrometry; Detection limit; Liquid chromatography–mass spectrometry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002146015,0.0001367081,0.0003082252,0.00009045241,0.00007685224,0.00002438884,0.0001479434,0.00009411437,0.009227873],"category_scores_gemma":[0.0005730108,0.00005090236,0.0001873844,0.0009017523,0.00001074767,0.00007461146,0.00002936634,0.00003503713,0.000009827495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003409991,"about_ca_system_score_gemma":0.0000258701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001743583,"about_ca_topic_score_gemma":0.0002606956,"domain_scores_codex":[0.9989539,0.00008621801,0.0003074437,0.0002901841,0.0001716432,0.0001906516],"domain_scores_gemma":[0.9986048,0.0008413755,0.0002094342,0.00006722111,0.0001875867,0.00008955685],"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":[0.0001073429,0.0001077517,0.009563771,0.00009591251,0.0006224355,0.000003991407,0.00005725122,0.00003198445,0.9546732,0.00003680915,0.001143276,0.03355632],"study_design_scores_gemma":[0.0002807134,0.0002852904,0.1907402,0.0003571202,0.000241057,5.56985e-7,0.00008504763,0.000493028,0.800643,0.00004442491,0.006564922,0.0002646164],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9526449,0.0004538496,0.007164262,0.0004265416,0.00001473344,0.0004261034,0.03865196,0.00008924054,0.0001283539],"genre_scores_gemma":[0.9742786,0.000003524152,0.01916517,0.00005991769,0.00004137314,0.00009115037,0.006335579,0.0000016447,0.00002302869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1811765,"threshold_uncertainty_score":0.9916778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03445162001143569,"score_gpt":0.2790279029537898,"score_spread":0.2445762829423541,"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."}}