{"id":"W2116974243","doi":"10.5740/jaoacint.15021","title":"High Throughput Analytical Techniques for the Determination and Confirmation of Residues of 653 Multiclass Pesticides and Chemical Pollutants in Tea by GC/MS, GC/MS/MS, and LC/MS/MS: Collaborative Study, First Action 2014.09","year":2015,"lang":"en","type":"article","venue":"Journal of AOAC International","topic":"Pesticide Residue Analysis and Safety","field":"Agricultural and Biological Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Chemistry; Chromatography; Pesticide; European union; Gas chromatography–mass spectrometry; Pesticide residue; Environmental chemistry; Mass spectrometry; Business","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0146998,0.001058197,0.0009925157,0.003770021,0.001730486,0.001331158,0.002401149,0.002096149,0.0007293236],"category_scores_gemma":[0.003852323,0.001062271,0.00183198,0.002712496,0.001076069,0.001187321,0.002929201,0.0008840741,0.0006198945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001903356,"about_ca_system_score_gemma":0.003934581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005557742,"about_ca_topic_score_gemma":0.01270834,"domain_scores_codex":[0.9872662,0.002884346,0.0008825004,0.002640718,0.005725522,0.0006007759],"domain_scores_gemma":[0.9963533,0.0005514075,0.001055947,0.0007488228,0.001073925,0.000216687],"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":[0.0009894156,0.001748443,0.03125591,0.0008581554,0.0008219751,0.0003368584,0.0008133841,0.003008302,0.8900276,0.0004183679,0.001009585,0.06871206],"study_design_scores_gemma":[0.0006141035,0.008379183,0.1498779,0.0001358174,0.001247457,0.002656208,0.0008370321,0.01381931,0.8067017,0.0006223448,0.01481941,0.0002895684],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8815821,0.004599973,0.1025949,0.0003228451,0.00005339619,0.003152107,0.003710823,0.0009189597,0.00306496],"genre_scores_gemma":[0.6808079,0.003454665,0.3028938,0.0004079412,0.00003255741,0.002612504,0.006741313,0.0001255809,0.002923651],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0146998,"threshold_uncertainty_score":0.07774091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0294622096688201,"score_gpt":0.3092428456539509,"score_spread":0.2797806359851308,"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."}}