{"id":"W2280807903","doi":"10.5740/jaoacint.15-084","title":"Determination of β-N-methylamino-L-alanine, N-(2-aminoethyl)glycine, and 2,4-diaminobutyric acid in Food Products Containing Cyanobacteria by Ultra-Performance Liquid Chromatography and Tandem Mass Spectrometry: Single-Laboratory Validation","year":2015,"lang":"en","type":"article","venue":"Journal of AOAC International","topic":"Amino Acid Enzymes and Metabolism","field":"Biochemistry, Genetics and Molecular Biology","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"British Columbia Institute of Technology; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; British Columbia Institute of Technology","keywords":"Chromatography; Chemistry; Repeatability; Derivatization; Analyte; Liquid chromatography–mass spectrometry; Detection limit; Tandem mass spectrometry; Mass spectrometry; Selected reaction monitoring; Residue (chemistry); Hydrolysis; Biochemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.004816337,0.001584978,0.001026879,0.001450951,0.001133456,0.001024751,0.001112284,0.001383766,0.0003808277],"category_scores_gemma":[0.003945354,0.0006507108,0.0008627948,0.001175461,0.001092677,0.0005729374,0.000806827,0.0007209442,0.0004061213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001488773,"about_ca_system_score_gemma":0.002739709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007544292,"about_ca_topic_score_gemma":0.01893703,"domain_scores_codex":[0.993921,0.001381129,0.0005227537,0.001096164,0.002840446,0.0002384663],"domain_scores_gemma":[0.9972887,0.0004256169,0.000651932,0.0002017712,0.001301801,0.0001301896],"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":[0.0002020777,0.0001556473,0.005435926,0.0001129434,0.00007261516,0.00008178011,0.0001326656,0.0004999544,0.9893113,0.00004530217,0.00004386459,0.003905977],"study_design_scores_gemma":[0.00005882883,0.001640823,0.02590522,0.00006506468,0.0001254006,0.0005018112,0.0001501123,0.006174676,0.9633664,0.00008252274,0.001878227,0.00005100041],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9559875,0.001893599,0.03850735,0.0001336146,0.00005838875,0.0008426206,0.0008867366,0.0003397696,0.001350399],"genre_scores_gemma":[0.823842,0.002340343,0.1656468,0.0005507191,0.00003859785,0.002295931,0.001868242,0.0001277869,0.003289447],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.007544292,"threshold_uncertainty_score":0.02547151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01020880309118895,"score_gpt":0.2271546925491529,"score_spread":0.2169458894579639,"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."}}